Top Cybersecurity Threats of 2025 and How to Combat Them

As digital transformation accelerates across every sector, cybersecurity threats are evolving at an equally rapid pace. In 2025, attackers are harnessing artificial intelligence, automation, and the vulnerabilities of interconnected systems to launch more targeted, damaging, and scalable cybersecurity attacks than ever before.

From deepfake-driven social engineering to AI-poisoned data and compromised supply chains, today’s cybersecurity risks are more complex — and demand smarter, more adaptive cybersecurity defenses. This article explores the most pressing cyber threats of 2025 and outlines actionable strategies for detecting, preventing, and responding to them.

2025 Cybersecurity Threats: Quick Checklist

1. AI-driven phishing and social engineering
2. Ransomware-as-a-Service (RaaS) attacks
3. Supply chain vulnerabilities
4. Deepfake and voice cloning fraud
5. Zero-day exploitation at scale
6. Cloud misconfigurations and API exposures
7. AI model poisoning and data manipulation
8. IoT and OT (Operational Tech) attacks
9. Insider threats enhanced by automation
10. Credential stuffing and passwordless attack vectors

1. AI‑Powered Phishing & Social Engineering

The Rise of Intelligent Phishing

Phishing isn’t just about suspicious emails anymore. In 2025, it’s increasingly powered by artificial intelligence, making it faster, more convincing, and significantly harder to detect. This evolution has turned phishing into a serious cybersecurity concern for every organization. Attackers are using large language models (LLMs) and deep learning to create personalized messages, imitate executives, and manipulate employees with alarming precision.

According to a 2024 report by DeepStrike, 3.4 billion phishing emails are sent every day, accounting for 1.2% of all global email traffic. What’s changed is the success rate: messages crafted using AI had a 54% click-through rate, compared to 12% for those written by humans.

In one simulated experiment conducted by IBM X-Force, generative AI models were used to craft spear-phishing emails against C-level personas. The campaign achieved a 70% open rate and 49% engagement rate — a level of precision-driven manipulation rarely seen before.For security leaders, countering AI-powered phishing requires layered cybersecurity defenses, advanced detection tools, and ongoing employee training. In this new threat landscape, human awareness remains a critical piece of the cybersecurity puzzle.

How AI Is Reshaping Social Engineering

Attackers use AI to:

• Scrape public data (LinkedIn, GitHub, X, company pages) to craft highly contextual messages.
• Mimic language patterns and tone of internal communication using generative AI.
• Clone voices and images for real-time video or phone-based impersonation, especially in business email compromise (BEC) and executive fraud schemes.
• Automate entire phishing campaigns, including follow-ups, fake login portals, and redirection tactics — all dynamically generated.

In January 2025, a European financial institution reported a case in which a generative AI system was used to impersonate the voice of the CFO in a deepfake call, authorizing a fraudulent $6.1 million transfer. The call included personal details, timing references, and urgency — all synthesized using leaked internal emails and public information.

Evolving Tactics: Beyond Email

Phishing is no longer just an email problem. In 2025, we see these vectors gaining traction:

• SMS and messaging apps (WhatsApp, Telegram, Slack) used in credential harvesting.
• Deepfake video calls and real-time face-swapping during remote meetings.
• AI-generated websites mimicking internal portals (e.g., HR tools, login dashboards) with pixel-perfect fidelity.
• Voice cloning in callback phishing scams, targeting helpdesks or financial teams.

This convergence of AI + social engineering is not just dangerous — it’s scalable.

How to Defend Against AI-Powered Phishing

Defending against these attacks requires a layered, proactive approach that blends technology, training, and policy:

1. Deploy AI-Augmented Email Security

• Traditional spam filters are not enough. Platforms like Abnormal Security, Cofense, or Darktrace use behavioral analysis to detect anomalous tone, context, or message flow.
• According to Cofense, their AI-driven system detected and blocked a malicious email every 42 seconds in late 2024.

2. Phishing Simulations & Continuous Awareness

• Routine phishing simulations help employees recognize realistic attacks.
• According to a KnowBe4 study, organizations that conducted monthly simulations saw a 96% improvement in phishing identification over 6 months.

3. Zero Trust and Multi-Factor Authentication (MFA)

• Always verify — even internal communications.
• Adopt zero trust principles that enforce identity, location, and context verification before granting access.
• Use phishing-resistant MFA methods (e.g., FIDO2 keys or biometrics).

4. Secondary Channel Verification

• Especially for financial transfers or sensitive requests, use a second channel (e.g., phone call or secure chat) for confirmation.
• Ensure that verification steps include voice validation protocols, especially in executive-level operations.

5. Monitor the Web for Impersonation

• Monitor dark web forums, AI-generated media platforms, and cloned domains for brand abuse or executive impersonation.
• Consider services like ZeroFox, CybelAngel, or BrandShield for this task.

Phishing in 2025 is no longer driven by poor grammar and fake Nigerian princes. It’s led by AI models that write better than most humans, equipped with real-time personalization and capable of mimicking real identities with chilling accuracy — making it a fast-evolving cybersecurity threat.

For CISOs and IT leaders, the challenge isn’t just identifying malicious emails — it’s preparing employees and systems for synthetic attacks that sound and look real, and understanding how social engineering now intersects with broader cybersecurity risks.

Adopting AI-driven defense, practicing zero trust, and building a culture of verification and skepticism are no longer optional — they’re the front line of modern cybersecurity.

2. Ransomware‑as‑a‑Service (RaaS)

The Industrialization of Cyber Extortion

Ransomware is no longer the work of lone hackers or small groups. In 2025, it has evolved into a professionalized, profit-driven cybersecurity threat — a business model called Ransomware-as-a-Service (RaaS).

Under the RaaS model, ransomware developers sell or lease their malware to affiliates, who carry out the actual attacks in exchange for a share of the profits. This franchise-style approach has drastically lowered the barrier to entry and fueled a global surge in cybersecurity incidents across sectors.

For organizations, defending against ransomware is no longer just an IT concern — it requires coordinated cybersecurity strategies that combine prevention, detection, response, and resilience.

In the first half of 2024 alone, over 2,200 organizations were listed on ransomware leak sites—a 35% increase from the previous quarter. Industrial sectors, including manufacturing, energy, and healthcare, remain prime targets.

Ransomware in 2025: By the Numbers

• 72.7% of organizations were hit by ransomware in 2023, up from 66% the previous year.
• The average ransom payment rose to $5.2 million in 2024, more than double the 2022 figure.
• LockBit, BlackCat (ALPHV), and Clop accounted for nearly 70% of RaaS-related attacks in late 2024.

The RaaS Supply Chain

RaaS attacks are no longer “smash-and-grab” operations. They are structured and sequenced, often involving:

1. Initial access brokers (IABs) who sell credentials or backdoor access.
2. Ransomware affiliates who rent malware kits (e.g., LockBit, Black Basta).
3. Leak site operators who publish stolen data to apply pressure.
4. Negotiation specialists who manage ransom conversations with victims.

This model allows for specialization, scalability, and outsourcing, making it easy for non-technical criminals to participate in cyber extortion.

For example, in December 2024, the Medusa RaaS group reportedly targeted 83 organizations in 17 countries within a 3-week span. Many affiliates used stolen VPN credentials, leaked in prior breaches, to bypass detection.

Double, Triple, and Quadruple Extortion

Modern ransomware campaigns employ multi-layered extortion tactics:

• Double extortion: Data is encrypted and exfiltrated. Pay or your data goes public.
• Triple extortion: Attackers also target your customers, partners, or patients.
• Quadruple extortion: Attackers threaten DDoS attacks or regulatory exposure (e.g., GDPR fines).

In a 2024 case targeting a European pharma firm, attackers encrypted files, leaked patient data, threatened regulators, and launched a DDoS attack during negotiations — quadruple extortion in action.

Why RaaS Keeps Growing

• High ROI: Ransomware yields millions, with minimal up-front investment.
• Low risk of prosecution, especially when attackers operate from countries with limited cybercrime enforcement.
• Rising availability of IABs and initial access services on darknet forums.
• Sophisticated automation tools that streamline lateral movement, encryption, and exfiltration.

How to Defend Against RaaS

1. Segmentation and Zero Trust

• Divide networks into trust zones; don’t allow ransomware to spread laterally.
• Apply zero trust architecture (ZTA) principles to limit access dynamically.

2. Immutable, Offsite Backups

• Maintain offline or cloud-isolated backups.
• Perform regular restore tests — backups are useless if you can’t recover quickly.

3. Endpoint and Extended Detection & Response (EDR/XDR)

• Invest in tools that detect behavior anomalies, not just known malware signatures.
• Detect early-stage actions like lateral movement, privilege escalation, or unusual encryption patterns.

4. Email and Access Hardening

• Use phishing-resistant MFA (e.g., hardware tokens, biometric auth).
• Scan inbound emails and attachments with sandboxed AI filters (e.g., Proofpoint, Abnormal Security).

5. Patch Management and Vulnerability Prioritization

• Many RaaS attacks exploit known vulnerabilities (e.g., VPN, RDP, and file transfer software).
• Automate vulnerability scanning and prioritize patching based on asset exposure.

6. Incident Response Playbooks

• Prepare for attacks in advance with IR workflows and communication trees.
• Include legal, PR, technical, and executive stakeholders in tabletop exercises.

Real-World Tip: Monitor Leak Sites Proactively

Monitor ransomware leak sites for mentions of your organization or industry sector. Tools like CyberSixgill, Recorded Future, or ShadowDragon can help you spot early signs of compromise or sector targeting.

Ransomware-as-a-Service has transformed cyber extortion into an organized criminal economy, targeting organizations large and small, with increasing precision and speed.

What was once a “technology problem” is now a business continuity crisis. The good news? With proper investment in detection, segmentation, and recovery — and by treating ransomware readiness as a board-level issue — organizations can dramatically reduce their risk of disruption.

At Fyld, we help companies implement tailored anti-ransomware strategies, including:

• Threat surface audits
• Backup & recovery stress testing
• Red team simulations
• EDR/XDR solution design
• Incident response planning
  

3. Supply Chain Vulnerabilities

The Weakest Link in a Hyperconnected World

In 2025, cybercriminals are no longer targeting just you — they’re targeting everyone you rely on. From SaaS providers and third-party APIs to firmware vendors and CI/CD pipelines, the digital supply chain has become one of the most exploited vectors in modern cybersecurity.

Attackers compromise trusted partners to bypass your defenses and infiltrate your systems under the radar. This strategy, known as supply chain compromise, is not only effective — it’s increasingly automated, AI-assisted, and reshaping the cybersecurity risk landscape.

For many organizations, securing the supply chain is now one of the most complex and urgent cybersecurity priorities.

According to a 2024 report by the European Union Agency for Cybersecurity (ENISA), supply chain attacks increased by 42% year-over-year, with a growing trend of attackers targeting software libraries and open-source dependencies.

Notable Supply Chain Incidents

• MOVEit Breach (2023–2024): Attackers exploited a vulnerability in Progress Software’s MOVEit file transfer tool. Over 2,000 organizations — including government agencies and global corporations — had data stolen. The breach was traced back to the Clop ransomware group, operating via a zero-day in third-party infrastructure.
• 3CX Desktop App Hack (2023): Hackers inserted malicious code into a trusted desktop VoIP app. The breach began through a compromised software vendor in the company’s upstream development chain. The malware remained undetected for weeks, affecting tens of thousands of clients globally.
• SolarWinds (2020–2025 Fallout): Though it began in 2020, the SolarWinds compromise continues to echo today. The attacker (suspected to be state-sponsored) gained access to U.S. government networks via poisoned updates in a widely used IT management platform — proving that trust in digital supply chains can be catastrophic when misplaced.

Why Supply Chain Attacks Work

1. Trust is inherited: Organizations implicitly trust their vendors’ code and services.
2. Visibility is limited: Most companies lack full transparency into third-party risk or transitive dependencies.
3. Security gaps vary: Even if your defenses are strong, your suppliers may not follow the same standards.
4. Attack surface is sprawling: APIs, SDKs, CI/CD pipelines, IaC scripts — all are now potential points of entry.

Where Attackers Focus in 2025

• Open-source libraries: Injecting malicious dependencies into popular packages (e.g., npm, PyPI, Maven).
• CI/CD environments: Targeting build pipelines to inject malware before release.
• API integrations: Exploiting insecure or over-privileged third-party APIs.
• Firmware vendors: Compromising hardware providers that are assumed to be “trusted by design.”
• Logistics and OT supply chains: Targeting manufacturing partners with outdated systems and lax controls.

A report by ReversingLabs in Q1 2025 found that 1 in 8 open-source components used in enterprise apps contained critical vulnerabilities or malicious code.

How to Defend Against Supply Chain Threats

1. Demand SBOMs (Software Bill of Materials)

• Require all software providers to share a list of dependencies and third-party code.
• Use tools like Syft, CycloneDX, or Dependency-Track to manage and audit SBOMs.

2. Continuous Third-Party Risk Assessments

• Conduct security assessments not just before onboarding vendors — but continuously.
• Use platforms like SecurityScorecard, BitSight, or UpGuard to monitor vendor posture.

3. Secure CI/CD and DevSecOps Pipelines

• Implement signed builds, access controls, and artifact integrity validation.
• Scan for secrets, misconfigurations, and vulnerable components in the build process using tools like Checkov, Snyk, or SonarQube.

4. Network Segmentation and Least Privilege

• Don’t give third-party software more access than it absolutely needs.
• Apply strict IAM and network segmentation, especially for software with backend or admin permissions.

5. Behavioral Monitoring and Anomaly Detection

• Even trusted software can be abused. Monitor for abnormal behavior from all apps and integrations.
• Use EDR/XDR systems with behavior analytics to flag anomalies early.

Proactive Steps for IT Leaders

• Map your supply chain: Identify and classify all third-party and fourth-party vendors.
• Implement zero trust at the integration level: Don’t allow implicit trust between applications.
• Simulate breach scenarios that begin with a compromised partner — not a direct attack.

In 2025, you are only as secure as your least-secure vendor. Supply chain attacks exploit the inherent trust baked into how we build, ship, and consume digital services — often with devastating results.

Whether it’s through a single open-source library or a trusted SaaS integration, attackers can reach deep into your network without ever “targeting” you directly.

At Fyld, we help organizations:

• Assess and secure digital supply chains
• Implement secure DevSecOps practices
• Build SBOM and open-source governance frameworks
• Evaluate third-party risks across software, cloud, and hardware ecosystems

Want to know your third-party exposure risk? Let Fyld’s cybersecurity team assess and strengthen your supply chain security. Visit www.fyld.pt to get started.

4. Deepfake & Voice-Cloning Fraud

When You Can’t Trust What You Hear — or See

Cybercrime in 2025 has entered an unsettling new phase: attackers now create synthetic people. With the help of generative AI, fraudsters are using deepfakes and voice cloning to impersonate executives, manipulate employees, and orchestrate high-stakes social engineering attacks that are almost indistinguishable from legitimate communication.

These tactics represent a growing cybersecurity challenge, blurring the line between human and machine-driven deception.

For organizations, protecting against synthetic identity fraud is no longer just a technical issue — it’s a fundamental cybersecurity and trust concern.

In this evolving threat landscape, employee awareness, identity verification protocols, and AI-powered detection must become core elements of your cybersecurity strategy.

In many cases, victims aren’t just fooled — they never realize they were defrauded until it’s too late.

The Rise of Deepfake Cybercrime

• In 2024, the number of deepfake fraud incidents surged by 900%, according to Sensity AI’s global fraud tracking report.
• A Gartner survey in Q4 2024 revealed that 78% of large enterprises experienced at least one attempted deepfake-related fraud attack in the previous year.
• By early 2025, synthetic media tools had become so accessible that even small criminal groups could generate realistic voice clones in under 5 minutes, using only a short audio sample and open-source tools like ElevenLabs or Respeecher.

Real-World Attacks

• $25.6 Million Deepfake Scam (Hong Kong, 2024): A finance employee at a multinational firm transferred $25.6 million after a deepfake video call that included several “colleagues” — all generated synthetically. The attackers cloned the CFO’s voice and visual likeness with near-perfect accuracy.
• UK-based Hedge Fund (2023): Voice cloning was used in a fake emergency call that convinced a junior analyst to fast-track a large crypto transfer. Forensics revealed that less than 90 seconds of public speaking footage had been used to create the cloned voice.
• Fake CEO Speeches and Investor Scams: In late 2024, several fraudulent videos featuring deepfake CEOs announcing fake mergers and acquisitions led to stock price volatility and insider trading probes — showing that deepfake fraud now extends to market manipulation.

Why It Works

• Believability: AI-generated voices and faces are more realistic than ever. They can replicate subtle details — cadence, intonation, even emotion.
• Speed and Accessibility: Public figures’ voices and images are widely available on YouTube, LinkedIn, and internal webinars.
• Contextual Targeting: Threat actors pair deepfakes with prior email compromise or leaked meeting notes to create incredibly believable scenarios.

In a 2024 survey by Medius, 87% of finance professionals admitted they would authorize a payment if contacted by a voice they believed to be their CEO or CFO — even when warned about the possibility of deepfakes. Entrust’s 2025 Identity Fraud Report found that deepfakes now account for 40% of all biometric fraud attempts, and synthetic voice scams occur as frequently as every five minutes. These numbers highlight just how easy it is for attackers to weaponize trust, especially when synthetic voices sound indistinguishable from the real thing.

How to Defend Against Deepfake & Voice-Cloning Fraud

1. Establish Secondary Verification Channels

• Never authorize financial or sensitive actions based solely on voice or video confirmation — no matter how convincing.
• Require out-of-band confirmation via secure channels (e.g., verified mobile apps, internal chat with known fingerprints).

2. Train Staff for Deepfake Awareness

• Conduct internal drills simulating deepfake-based fraud.
• Teach employees to recognize contextual red flags (urgency, uncharacteristic behavior, tone mismatch).

3. Use Deepfake Detection Tools

• Deploy AI tools capable of analyzing videos for synthetic markers. Tools like Reality Defender, Deepware, and Microsoft’s Video Authenticator can flag altered content.
• Monitor for impersonations across platforms using services like PimEyes, ZeroFox, or CybelAngel.

4. Limit Publicly Available Executive Media

• Restrict public video/audio of top executives, particularly in high-risk industries like finance, healthcare, and government.
• Use controlled messaging and watermark executive speeches to discourage scraping and misuse.

5. Adopt Identity Verification Protocols

• For critical actions (payments, new vendor setups, mergers), require multi-step identity checks that go beyond appearance or voice:
  • Cryptographically signed requests
  • Authenticated tokens (e.g., YubiKey)
  • Facial liveness detection (resistant to video injection)

Proactive Monitoring

• Monitor dark web forums for mentions of your leadership, particularly in conjunction with “AI clone,” “video spoof,” or “voice mimic.”
• Regularly scan for fake profiles or synthetic media impersonating your brand — especially on LinkedIn, X, and YouTube.

In 2025, seeing is no longer believing — and hearing isn’t either.

Deepfake and voice cloning attacks have escalated from novelty to a mainstream fraud vector, capable of bypassing both human intuition and technical filters. Organizations must now train, verify, and monitor with the assumption that synthetic content is a threat — not a theoretical risk.

Fyld helps businesses implement safeguards against impersonation attacks, including:

• Executive impersonation risk assessments
• Synthetic media detection systems
• Deepfake-aware security training for finance, HR, and executive assistants
• Multi-layered identity verification processes

5. Zero‑Day Exploits at Scale

The Race Between Disclosure and Destruction

In cybersecurity, timing is everything — and in 2025, zero-day vulnerabilities are being weaponized faster than ever before. A “zero-day” is a flaw unknown to the software vendor and users — meaning there’s zero time to patch or respond before exploitation begins.

Today’s threat actors, including state-sponsored groups and criminal enterprises, use automated scanning tools, AI-powered reconnaissance, and pre-positioned malware to launch widespread attacks within hours — sometimes minutes — of vulnerability discovery.

The Scale of the Problem

• According to Mandiant, zero-day exploits increased 67% in 2024 — from 55 in 2023 to 92 documented cases.
• Google’s Threat Analysis Group reported that over 40% of all zero-day exploits in 2024 targeted enterprise platforms such as Microsoft Exchange, Google Workspace, and VMware ESXi.
• Threat actors now weaponize published vulnerabilities within 48 hours in nearly 1 out of 3 cases — sometimes using automation to deploy exploit kits before patches are even available.

And many of these vulnerabilities are not standalone — they’re chained together (e.g., privilege escalation + remote code execution) to maximize impact.

Notable Exploits from the Past Year

• CVE-2024-25153: A critical zero-day in Ivanti VPN appliances allowed remote code execution. Within 48 hours of disclosure, more than 1,400 enterprise instances were compromised, according to Rapid7.
• MOVEit SQL Injection (CVE-2023-34362): Though initially seen in 2023, exploitation of this zero-day continued well into 2024, with over 2,000 global victims including governments, banks, and airlines. The Clop ransomware group automated its scanning via Shodan and targeted file transfer systems at scale.
• Google Chrome Zero-Day (CVE-2024-3305): Exploited in the wild before Google’s patch release, the flaw affected billions of users and was weaponized via drive-by downloads embedded in compromised ad networks.

Why Exploitation Is Faster in 2025

1. AI Accelerates Vulnerability Discovery
   Language models and AI-powered fuzzers help attackers analyze patch diffs and reverse-engineer flaws.
2. Exploit Kits Go Commercial
   Zero-day exploits are sold on underground markets, sometimes as part of “exploit-as-a-service” platforms.
3. Cloud-First Environments Increase Exposure
   Misconfigured or exposed cloud services often give attackers a short but dangerous window to strike before detection tools catch up.
4. Automation for Reconnaissance
   Tools like Masscan, Shodan, and customized AI scrapers let threat actors scan millions of targets in minutes.

How to Defend Against Zero-Day Exploits

1. Implement Virtual Patching and Runtime Protections

• Use Web Application Firewalls (WAFs) and Runtime Application Self-Protection (RASP) to block known patterns of exploitation even when the underlying vulnerability isn’t patched yet.

2. Adopt Real-Time Threat Intelligence

• Subscribe to feeds like CISA KEV (Known Exploited Vulnerabilities), MISP, or Recorded Future to prioritize mitigation efforts based on real-world threat activity — not just CVSS scores.

3. Automate Patch Management and Asset Visibility

• Maintain a complete and updated asset inventory. If you don’t know what you have, you can’t protect it.
• Use tools like Qualys, Rapid7, or Tenable to automate vulnerability scanning and prioritize based on exploitability.

4. Apply Least Privilege and Network Segmentation

• Even if exploitation occurs, limit what the attacker can access by enforcing least privilege, role-based access controls, and network segmentation (especially for high-value systems like Active Directory, finance, or OT environments).

5. Deploy EDR/XDR with Behavior-Based Detection

• Zero-day exploits often exhibit anomalous behavior (e.g., privilege escalation, memory injection, unusual DLL calls).
• Solutions like CrowdStrike, SentinelOne, or Microsoft Defender for Endpoint can detect these behaviors even without a known signature.

Organizational Readiness: Tabletop It

Simulate a zero-day incident as part of your cybersecurity incident response exercises.

Test how fast your teams can detect, triage, and isolate systems when there is no patch or IOC available — a critical cybersecurity capability in today’s threat landscape.

Include legal, PR, and executive teams in your playbooks — regulatory reporting timelines are getting shorter under frameworks like NIS2 and DORA.

Zero-day attacks are no longer the exclusive domain of state actors or cyberwarfare teams — they’ve become commoditized, scalable, and increasingly automated. Every organization must now assume that at least one system in their environment is exploitable at any given moment, making proactive cybersecurity readiness essential.

Resilience in 2025 doesn’t come from preventing every breach — it comes from being able to detect, isolate, and recover faster than attackers can escalate.

Fyld can help you:

• Build proactive patch and exploit management workflows
• Implement behavior-based endpoint protection
• Simulate zero-day attack scenarios with your teams
• Align your posture with global frameworks like NIS2 and ISO/IEC 27001

6. Cloud Misconfigurations & API Exposures

The New Perimeter Is Everywhere — and Often Misconfigured

Cloud adoption is no longer a competitive edge — it’s the foundation of modern IT. But as organizations rapidly deploy services across AWS, Azure, and GCP, many leave the front door open: cloud misconfigurations and insecure APIs are among the most common and costly cybersecurity gaps in 2025.

The flexibility of cloud architecture is its biggest strength — and its biggest liability. Whether it’s an over-permissive identity policy, an unprotected S3 bucket, or an exposed API endpoint, misconfigurations are now a primary entry point for cyber attackers and a growing cybersecurity concern.

In a hyperconnected environment, every misstep in configuration, access control, or monitoring adds to your organization’s overall cybersecurity risk profile.

Cloud Breaches by the Numbers

• According to the IBM X-Force Threat Intelligence Index, 82% of cloud security incidents were linked to misconfigured services or exposed APIs in 2024.
• The Gartner 2025 Cloud Security Survey shows that more than 70% of enterprises experienced at least one cloud-related security event in the past 12 months.
• The average cost of a cloud misconfiguration breach in 2025 is estimated at $4.47 million, according to Varonis.

The issue isn’t the cloud itself — it’s how organizations configure, monitor, and govern their cloud resources.

Real-World Incidents

• Toyota (2024): API keys embedded in public GitHub repositories exposed the personal data of over 260,000 customers on the T-Connect platform. The keys had been accessible for nearly five years before detection.
• Microsoft AI Research Exposure (2024): A misconfigured Azure Blob Storage bucket used by Microsoft’s AI team leaked 38TB of sensitive internal data, including credentials, private keys, and employee backups.
• Capita (2023): Attackers gained access to Microsoft 365 via misconfigured identity permissions, exposing sensitive government client data and triggering investigations into the firm’s compliance practices.

Common Misconfiguration Types in 2025

1. Over-permissive IAM roles
   Policies with *:* permissions or admin access across environments are still alarmingly common.
2. Publicly exposed storage buckets
   Buckets on AWS S3, Azure Blob, and Google Cloud Storage often default to private — but misconfigured sharing settings make them public.
3. Unauthenticated or overexposed APIs
   APIs without proper authentication, input validation, or rate limiting expose backends to injection, enumeration, or brute-force attacks.
4. Hardcoded secrets in source code
   API keys, tokens, and cloud credentials found in GitHub repos or developer sandboxes still rank among the top root causes of breaches.
5. Lack of logging and encryption
   Unmonitored services or unencrypted data-at-rest can allow undetected access and regulatory non-compliance.

Why Attackers Love Cloud Misconfigurations

Attackers exploit cloud weaknesses at scale using automation — turning overlooked cybersecurity gaps into entry points:

• Tools like Shodan, Censys, and GrayHatWarfare continuously scan for open ports, exposed buckets, and API endpoints.
• Credential stuffing and brute-force attacks are launched against poorly protected API logins, exposing critical cybersecurity vulnerabilities.
• Open-source recon tools (e.g., CloudSploit, Pacu, ScoutSuite) are used to identify misconfigurations inside cloud accounts once initial access is gained.

In 2024, attackers increasingly relied on “living off the cloud” — abusing native services like AWS Lambda or Azure Functions to carry out lateral movement, data exfiltration, and privilege escalation without triggering traditional cybersecurity perimeter defenses.

Defense Strategy: How to Secure Your Cloud & APIs

1. Enforce the Principle of Least Privilege (PoLP)

• Avoid blanket access policies and default admin privileges.
• Use role-based access controls and time-bound credentials.
• Audit IAM roles regularly using tools like AWS IAM Access Analyzer or GCP Policy Analyzer.

2. Automate Configuration and Compliance Audits

• Deploy Cloud Security Posture Management (CSPM) platforms such as:
  • Prisma Cloud
  • Wiz
  • Microsoft Defender for Cloud
  • Tenable Cloud Security
• Integrate configuration checks directly into CI/CD pipelines using tools like Checkov, TFSec, and OPA/Gatekeeper.

3. Secure and Monitor APIs

• Require strong authentication and enforce least privilege scopes.
• Apply rate limiting, input validation, and API gateway policies to prevent abuse.
• Use API security tools like Salt Security or Noname Security to monitor and defend your API estate.

4. Scan Code for Secrets and Vulnerabilities

• Use tools like GitGuardian, TruffleHog, or Gitleaks to detect exposed secrets and tokens in source code before they’re pushed to production.

5. Enable Centralized Logging and Real-Time Detection

• Use SIEM/XDR platforms (e.g., Splunk, Microsoft Sentinel, Sumo Logic) to aggregate and analyze cloud telemetry.
• Activate and monitor cloud-native logging (AWS CloudTrail, Azure Monitor, GCP Cloud Logging).
• Set up alerts for abnormal behavior like:
  • New IAM users with elevated privileges
  • Changes to storage permissions
  • Sudden spikes in API requests

Don’t Overlook Shadow Cloud

“Shadow cloud” — services deployed without IT’s approval — is a growing cybersecurity risk. Developers spin up resources in personal accounts or unvetted tools that fall outside the security perimeter. Combat this with:

• Regular DNS, subdomain, and IP scans
• Cloud discovery tools (e.g., Zscaler, Cisco Umbrella)
• Strict governance policies and DevOps training

Cloud misconfigurations and API exposures aren’t sophisticated zero-days — they’re avoidable cybersecurity lapses. But when overlooked, they give attackers a direct line to your sensitive data, systems, and users.

In 2025, securing the cloud isn’t just an IT task — it’s a core cybersecurity responsibility that requires constant visibility and discipline across teams.

The cloud doesn’t eliminate security responsibility — it redefines it. In 2025, protecting cloud infrastructure and APIs means:

• Automating guardrails
• Enforcing identity boundaries
• Continuously monitoring what you expose to the world

At Fyld, we help enterprises design and secure their cloud infrastructure, build automated compliance pipelines, and monitor API ecosystems — turning your cloud from a liability into a resilient advantage.

7. AI Model Poisoning & Data Manipulation

The Silent Sabotage of Artificial Intelligence

As artificial intelligence becomes deeply embedded in core business processes — from fraud detection and credit scoring to HR screening, healthcare diagnostics, and customer service — a new class of cybersecurity threat has emerged: attacks that target the models themselves.

In 2025, AI model poisoning and data manipulation are no longer theoretical risks. They represent one of the most insidious forms of cybersecurity attack — capable of corrupting predictions, undermining trust, and introducing long-term systemic failure, often without immediate visibility.

These model-level threats blur the line between AI innovation and cybersecurity risk, forcing organizations to rethink how they evaluate, deploy, and secure AI systems.

Securing AI models is no longer a niche technical challenge — it’s a fundamental cybersecurity requirement for protecting business integrity and customer safety. Organizations that fail to account for AI vulnerabilities will face a widening cybersecurity gap as attackers target not just infrastructure, but decision-making itself.

These attacks don’t compromise infrastructure. They compromise logic.

The Threat by the Numbers

• According to Gartner’s 2025 Emerging Risks Report, 53% of organizations using AI models in productionexperienced some form of data or model integrity incident in the past 18 months.
• MITRE ATLAS, a framework for adversarial threats against AI, logged a 39% increase in attack activity targeting machine learning systems between 2023 and 2024.
• Despite rising adoption, only 31% of enterprises have implemented formal processes for AI security auditing or adversarial testing.

What Is AI Model Poisoning?

There are two main categories of attack:

1. Training-Time Attacks (Data Poisoning)

Attackers inject manipulated, mislabeled, or malicious samples into a model’s training dataset. The goal is to subtly distort its learning process so it behaves incorrectly — but only in specific conditions, creating hidden cybersecurity risks that are difficult to detect.

This type of model poisoning represents an emerging frontier in cybersecurity, where AI manipulation introduces vulnerabilities that traditional defenses often miss.

For example: A vision model in a self-driving car might learn to ignore a certain shape or color of stop sign under manipulated training data — a scenario researchers have successfully demonstrated in controlled cybersecurity research environments.

As AI adoption accelerates, organizations must treat model integrity as a core cybersecurity priority, with testing and monitoring integrated into broader cybersecurity programs.

Ignoring these risks leaves organizations exposed to long-term cybersecurity failures that may go unnoticed until real-world consequences occur.

2. Inference-Time Attacks (Prompt Injection, Model Manipulation)

These attacks happen when a malicious input is crafted to manipulate the output of a trained model. In LLMs, this could involve hiding instructions in documents or text that cause the model to ignore safety rules, leak private information, or give unintended advice.

A growing vector in 2025: prompt injection embedded in PDFs, code comments, or user-generated content, designed to trigger misbehavior in GPT-based internal copilots or agents.

Real-World Examples

• Medical ML Sabotage (2024): A research team successfully manipulated a breast cancer diagnostic model by inserting just 112 poisoned images into a training dataset of 100,000. The result? The model misclassified benign tumors as malignant 18% more often — with no code-level changes required.
• GitHub Prompt Injection (2024): Researchers showed how LLM-powered code assistants could be manipulated to write insecure code by hiding toxic prompts inside open-source repositories’ README files. The LLM responded to the hidden prompt, not the user’s intended question.
• AI Voice Cloning Backdoor: A startup’s speech recognition model was subtly altered by a contributor to ignore speaker verification protocols under specific phrasing — allowing deepfake audio to bypass biometric authentication.

Why This Threat Is Different

• It’s invisible: Traditional endpoint detection, SIEM, or antivirus tools won’t flag poisoned training data or malformed prompts — creating hidden cybersecurity risks that often go undetected.
• It lingers: A poisoned model might remain in use for months or years, slowly introducing faults or failures that quietly undermine cybersecurity integrity.
• It scales: Attacks on shared models, datasets, or APIs can affect hundreds or thousands of systems simultaneously.

And because many models are hosted via APIs or consumed as black-box services (e.g., GPT-4, Claude, Gemini), organizations may not even know their models are vulnerable — or already compromised.

Top Attack Vectors in 2025

• Public dataset poisoning (e.g., through GitHub, Reddit, Wikipedia contributions)
• Prompt injection in files, user forms, or comments consumed by AI agents
• Backdoored pre-trained models from open repositories (e.g., Hugging Face)
• Data manipulation via third-party annotation services
• Model extraction followed by inversion (learning proprietary behavior from outputs)

How to Defend Against AI Model Poisoning

1. Validate and Secure All Data Pipelines

• Require data lineage and version control for all training sets.
• Scan for label inconsistencies, anomalies, and statistical outliers.
• Avoid training or fine-tuning on unvetted, crowdsourced, or scraped data.

2. Monitor and Restrict Model Access

• Limit who can modify, fine-tune, or deploy models — including third-party contractors.
• Use role-based access controls (RBAC) and audit logs for model pipelines.
• Treat models as sensitive assets — the same way you protect source code or databases.

3. Run Red Team Simulations and Adversarial Testing

• Use open-source tools like IBM Adversarial Robustness Toolbox, SecML, or Microsoft Counterfit to simulate poisoning or inference attacks.
• Include prompt injection tests for LLM-based applications in security QA.

4. Monitor Model Behavior Over Time

• Use model explainability techniques (e.g., SHAP, LIME) to detect changes in prediction logic.
• Compare new model behavior against baselines — retraining shouldn’t introduce unexplained shifts.
• Implement confidence threshold monitoring: sudden spikes in model certainty or uncertainty can signal compromise.

5. Harden APIs That Serve Models

• Rate-limit and authenticate API calls to inference services.
• Log all queries and track anomalies (e.g., repetitive phrasing, probing behavior).
• Isolate LLMs from directly executing system commands or modifying critical data without a human loop.

Organizational Strategy

• Incorporate AI risk into enterprise threat modeling and governance frameworks.
• Align with international guidelines like:
  • ISO/IEC 23894 for AI risk management
  • NIST AI Risk Management Framework
  • MITRE ATLAS attack patterns for AI
• Train DevSecOps teams to manage model lifecycles — not just code.

Cybersecurity in 2025 isn’t just about defending systems — it’s about defending intelligence.

Attackers have discovered that by poisoning the very data and logic your systems learn from, they can create slow-moving, stealthy, and highly effective compromises. These attacks are subtle, scalable, and incredibly difficult to detect with traditional tooling.

Organizations embracing AI must now embrace AI-specific security disciplines.

At Fyld, we help businesses:

• Assess model exposure and integrity
• Simulate poisoning and injection scenarios
• Build secure ML pipelines with audit and governance controls
• Harden LLM-based applications against prompt manipulation

8. IoT & OT System Attacks

When the Physical World Becomes a Cyber Target

n 2025, the convergence of IT and OT (Operational Technology) — once a strategic advantage — has become a major cybersecurity liability. From smart factories and connected medical devices to energy grids and autonomous vehicles, IoT and OT systems are increasingly under siege from both financially motivated actors and nation-state cybersecurity operations.

What makes this threat unique? These systems don’t just store data — they control the real world. A successful attack on a production line, hospital infusion pump, or power distribution node can disrupt critical infrastructure, endanger lives, and trigger cascading cybersecurity failures that extend far beyond a single organization.

Despite these risks, many industrial environments still lag behind in cybersecurity maturity, relying on legacy technologies, unpatched devices, and fragmented defenses.

In this environment, building resilient, secure-by-design IoT and OT ecosystems is no longer optional — it’s a cybersecurity imperative.

The Scale of the Threat

• According to Palo Alto Networks, attacks targeting OT environments rose 31% year-over-year in 2024, with the manufacturing, energy, and healthcare sectors hardest hit.
• Fortinet reported that 78% of OT organizations experienced at least one intrusion in the last 12 months, and 46% saw malware enter through IoT-connected devices.
• Cybersecurity and Infrastructure Security Agency (CISA) identified 9 critical ICS/SCADA vulnerabilities in 2024 that had no patches for months — highlighting persistent exposure in legacy systems.

And the cost? IBM’s 2024 report found that the average cost of a ransomware attack involving OT assets was $6.8 million, often requiring weeks to fully restore operations.

Real-World Examples

• Colonial Pipeline (ongoing fallout): While the original attack happened in 2021, continued copycat campaigns targeting pipeline infrastructure using ransomware variants like LockBit and BlackCat persist into 2025.
• Schneider Electric (2024): Threat actors exploited a vulnerability in Schneider’s EcoStruxure platform, allowing remote code execution on building automation systems across dozens of critical infrastructure sites in Europe.
• Düsseldorf University Hospital (Germany): An IoT-enabled DICOM imaging system was compromised, causing cascading failures across the hospital’s IT and OT networks. Patient services were delayed for 13 days.

These cases underscore a central truth: IoT and OT attacks don’t just disrupt digital systems — they interrupt physical reality.

What Makes IoT and OT Systems Vulnerable?

1. Legacy protocols
   Many OT devices still run on decades-old protocols (e.g., Modbus, DNP3) with no built-in encryption or authentication.
2. Flat network architectures
   Poor segmentation between IT and OT networks allows malware or attackers to pivot from email or cloud into plant operations.
3. Vendor lock-in and delayed patching
   Critical systems often rely on firmware updates from vendors — some of which can take months or are never released.
4. Device sprawl
   Organizations have thousands of unmanaged IoT devices — from HVAC controllers to security cameras — often invisible to security teams.
5. Hardcoded credentials and default settings
   Attackers scan for known factory passwords and exposed web interfaces to take over devices remotely.

Threat Actor Tactics in 2025

• Ransomware hitting OT directly: Groups like LockBit and Scattered Spider now include OT-aware payloads to encrypt PLCs and HMI terminals.
• Lateral movement from IT to OT: Attackers gain initial access via phishing or VPN, then pivot to connected OT networks using compromised domain controllers.
• Supply chain targeting: Malware injected through IoT firmware updates or compromised third-party ICS integrators.
• Remote hijacking: Exposed telnet ports, UPnP misconfigurations, and unsecured MQTT brokers allow real-time device takeover.

How to Defend IoT & OT Environments in 2025

1. Segment IT and OT Networks Rigorously

• Implement firewalls and DMZs between enterprise systems and industrial control networks.
• Use industrial-grade network segmentation with VLANs and protocol-aware gateways.

2. Conduct Full Asset Discovery and Visibility

• Use passive scanning tools like Nozomi Networks, Claroty, or Tenable.ot to map all devices and communication patterns.
• Maintain an up-to-date inventory of all connected IoT/OT assets, including firmware versions and communication ports.

3. Patch What You Can, Shield What You Can’t

• Prioritize patching for externally exposed devices or those with known vulnerabilities.
• Where patching isn’t possible, apply virtual patching or network-layer protections (e.g., intrusion prevention systems).

4. Enforce Least Privilege and Strong Authentication

• Eliminate shared credentials and require unique logins per device/operator.
• Use multifactor authentication for all remote access, including SCADA terminals and engineering workstations.

5. Monitor Behavior and Detect Anomalies

• Apply behavioral analytics to detect deviation in PLC/HMI instructions, command frequency, or communication patterns.
• Set real-time alerts for changes in firmware, configuration, or user access patterns.

6. Test Your Recovery Plan — With Hardware

• Include OT environments in business continuity and disaster recovery planning.
• Simulate ransomware or remote access scenarios in testbeds that mirror production environments.

Organizational Recommendations

• Assign clear ownership of OT security — often neglected in IT-centric cybersecurity teams.
• Train operations teams on basic cyber hygiene (e.g., USB safety, remote access protocols).
• Coordinate with vendors and integrators to enforce security-by-design in new industrial deployments.

And perhaps most critically: apply the same rigor to OT risk as you would to financial systems. Downtime in OT environments doesn’t just affect revenue — it can directly affect safety, compliance, and broader cybersecurity resilience.

IoT and OT systems were never designed with modern cyber threats in mind — yet they now represent some of the most high-value and high-risk digital assets in your environment.

In 2025, defending the factory floor, the grid, and the hospital wing requires a new mindset: cyber-physical resilience. This means bridging the gaps between IT and OT, between visibility and response, and between vendor assumptions and operational realities.

Important steps to help you organization:

• Conduct OT & IoT asset discovery and segmentation as a foundation for effective cybersecurity in industrial environments.
• Design secure-by-default ICS and BMS networks to reduce long-term cybersecurity risks.
• Implement OT-specific SIEM/XDR integrations to improve detection and response across your cybersecurity landscape.
• Train mixed IT/OT teams for incident response, ensuring both technical and operational staff are equipped to handle cybersecurity incidents.
• Assign clear ownership of OT security — often neglected in IT-centric security teams — to close critical cybersecurity gaps.
• Train operations teams on basic cyber hygiene (e.g., USB safety, remote access protocols), reinforcing frontline cybersecurity awareness.
• Coordinate with vendors and integrators to enforce security-by-design in new industrial deployments, embedding cybersecurity principles from day one.

9. Insider Threats Powered by Automation

When the Threat Comes from Within — and Scales

Not all cyberattacks begin outside your perimeter. In 2025, the insider threat is not only alive — it’s evolving. Powered by automation, AI-driven tools, and increasingly blurred lines between employees, contractors, and third-party access, insider threats have become faster, stealthier, and more scalable than ever — posing significant cybersecurity challenges.

The classic image of a rogue employee stealing data still applies. But in 2025, insiders also include accidentally misconfigured bots, overly-permissive automation scripts, and AI copilots that leak or modify data without oversight — all of which can create serious cybersecurity gaps.

These gaps aren’t limited to technical oversights — they represent business-critical cybersecurity vulnerabilities that attackers are actively exploiting.

Whether malicious or negligent, the insider of today has access to more systems, more data, and more tools — often without full visibility from security teams. That reality makes insider threat management a core component of any modern cybersecurity strategy.

Organizations that want to stay ahead must embed insider threat detection, identity governance, and behavioral monitoring into their broader cybersecurity programs.

The Impact in Numbers

• According to Ponemon Institute’s 2024 Cost of Insider Threats report, the average annual cost of insider-related incidents rose to $15.4 million, a 34% increase from 2022.
• 71% of organizations experienced at least one data loss or system compromise due to insider actions in the past year — up from 60% the year before.
• Gartner estimates that by the end of 2025, 25% of insider incidents will involve autonomous agents or AI-enhanced workflows that act without malicious intent but still cause damage.

What’s Changed in 2025

1. Automated insiders: Scheduled scripts, RPA bots, and AI assistants can exfiltrate data, alter records, or trigger system actions with no human supervision.
2. Third-party and hybrid workforce: Contractors, freelancers, and vendors often operate with elevated privileges — but outside internal cultural and compliance norms.
3. Blurred intent: Many insider incidents today are not malicious — they’re careless. Think of a marketing AI that uploads sensitive test data to public servers, or an engineer who shares an API key in a public GitHub repo.
4. AI copilots leaking data: As internal teams use LLM-based tools (e.g., ChatGPT, GitHub Copilot, internal GPT agents), proprietary data is increasingly shared or cached in ways that violate policies.

Real-World Cases

• Healthcare Access Abuse (2024): A hospital technician used automated data pulls from a records system to gather patient information, which was later sold to a third party. The automation made it look like routine system activity.
• Source Code Leak via LLM (2025): A junior developer unknowingly pasted internal code into a public AI tool for debugging. The model stored and reproduced proprietary logic in responses to unrelated users days later.
• Financial Bot Misconfiguration: A well-meaning RPA bot deployed in a global bank was granted broad access to customer accounts. A script error caused it to modify 18,000 records, requiring manual restoration and triggering regulatory fines.

How to Defend Against Insider Threats (Human & Automated)

1. Implement Least Privilege Access Control

• Enforce role-based access, remove default admin rights, and review entitlements quarterly.
• Apply just-in-time access and session expiration for high-privilege actions.

2. Monitor User and Entity Behavior (UEBA)

• Use platforms like Splunk UBA, Exabeam, or Microsoft Defender Insider Risk to detect unusual behavior: file access at odd hours, large downloads, or privilege escalation.
• Set up alerts for high-risk actions (e.g., bulk email exports, API key usage outside policy).

3. Identify and Govern Non-Human Identities

• Inventory all bots, RPA agents, and AI tools accessing data.
• Assign ownership, limit permissions, and log their activity like human users.

4. Train for Contextual Awareness

• Educate staff not just on phishing or password safety — but on the risks of AI tools, cloud sharing, and automation misuse.
• Simulate insider-style incidents during security awareness programs.

5. Encrypt and Monitor Sensitive Data

• Use DLP (Data Loss Prevention) tools to control how data moves across devices, email, and cloud storage.
• Apply encryption at rest and in transit, and ensure access is logged and reviewed.

6. Foster a Security-First Culture

• Encourage whistleblowing, anonymous reporting, and reward safe behavior.
• Promote psychological safety — employees who fear punishment are less likely to report mistakes.

Organizational Readiness Checklist

• Do you monitor both human and machine accounts?
• Do you know who can access your most sensitive data — and why?
• Are AI and automation tools reviewed before deployment?
• Are insider scenarios part of your tabletop exercises and response plans?

If not, it’s time to reframe insider risk not as a “people problem,” but as a privilege and visibility problem.

The Bottom Line

nsider threats in 2025 are no longer limited to disgruntled employees. They now include AI agents, over-permissioned bots, and negligent workflows — all capable of causing data loss, regulatory violations, or cybersecurity incidents at machine speed.

These evolving threats represent one of the most overlooked areas of cybersecurity risk. Whether intentional or accidental, insider-driven breaches can bypass even the most advanced cybersecurity defenses.

Security teams must shift from reacting to breaches to understanding behavior, managing identity risk, and governing automation — before insiders (or their tools) trigger tomorrow’s cybersecurity breach headlines.

In today’s complex environments, insider threat mitigation is not just an HR issue — it’s a critical cybersecurity priority that requires visibility, accountability, and collaboration across the business.

At Fyld, we help organizations:

• Build insider threat programs from policy to monitoring
• Secure human and non-human identities across hybrid environments
• Automate behavior analytics to detect early warning signs
• Develop incident response playbooks for AI and insider-driven scenarios

10. Credential Stuffing & Passwordless Attack Vectors

Authentication Under Attack: The Identity Crisis of 2025

Passwords were never a perfect solution. But in 2025, they’ve become one of the most actively abused — and most rapidly evolving — elements of modern cybersecurity. While many organizations are transitioning to passwordless authentication, attackers are adapting just as quickly, exploiting new identity systems and scaling old attack techniques like credential stuffing with unprecedented efficiency.

What’s changed? Billions of previously leaked credentials are now searchable, testable, and exploitable at scale using AI-driven bots and automation tools. At the same time, passwordless systems — often viewed as a silver bullet — introduce their own set of emerging cybersecurity risks.

The Threat Landscape by the Numbers

• The Akamai State of the Internet Report says that credential stuffing attacks rose by 84% in 2024, with over 42 billion login attempts recorded across major platforms.
• Over 65% of successful data breaches in 2024 involved stolen or reused credentials, according to Verizon’s DBIR 2024 report.
• 83% of organizations implementing passwordless solutions reported at least one attack attempt exploiting identity tokens or session hijacking, per a 2025 report from Ping Identity and IDSA.

What Is Credential Stuffing?

Credential stuffing is a brute-force tactic where attackers use large volumes of stolen credentials (typically from previous breaches) to attempt logins on other services, banking on users reusing the same passwords across platforms.

In 2025, threat actors now use:

• Machine learning bots that adapt login attempts based on response behavior
• Distributed attack infrastructure to bypass geofencing and rate limits
• Session replay tools that mimic legitimate browser/device behavior
• Account takeover-as-a-service offerings on darknet marketplaces

These aren’t script kiddies — they’re using enterprise-level automation.

Passwordless Doesn’t Mean Invulnerable

Passwordless authentication — based on biometrics, device-bound credentials, magic links, or push notifications — solves many traditional problems, but opens new ones:

• Session token theft via browser malware or man-in-the-middle (MitM) attacks
• Authentication fatigue and push notification spoofing (e.g., MFA bombing)
• Misconfigured SSO (Single Sign-On) that allows privilege escalation
• Phishing-resistant MFA bypass through stolen trusted devices or session cookies

In February 2025, a major European fintech was compromised after attackers cloned session cookies from a trusted developer device, bypassing passwordless and MFA controls entirely.

Real-World Examples

• ChatGPT Token Abuse (2024): Researchers discovered that session tokens stolen via browser extensions allowed unauthorized users to access corporate GPT accounts — including recent chats and prompt histories with sensitive data.
• Uber Push Bombing Incident (2023–2024): Attackers flooded a target with MFA prompts until they accepted out of frustration, granting access to internal tools. This technique — now widely known as MFA fatigue — remains highly effective.
• Passkey Hijacking via SIM Swap: In several 2024 cases, attackers used social engineering to perform SIM swaps, intercepting push-based logins or hijacking mobile-bound passkeys tied to biometric access.

How to Defend Against Credential and Identity-Based Attacks

1. Monitor for Compromised Credentials in Real Time

• Use tools like Have I Been Pwned, SpyCloud, or Google Cloud Identity Protection to scan for leaked usernames and passwords tied to your domain.
• Enforce automatic credential resets or lockouts for exposed accounts.

2. Implement Passwordless + Risk-Based Authentication

• Move to phishing-resistant passwordless methods like:
  • FIDO2 passkeys
  • Device-bound public key cryptography
  • Hardware tokens (e.g., YubiKey)
• Layer with risk-based policies that factor in geolocation, device hygiene, behavior anomalies, and time-of-access windows.

3. Protect Sessions and Tokens

• Apply short-lived access tokens with enforced re-authentication for sensitive actions.
• Monitor for token reuse or cookie replay attacks — especially in federated identity systems.
• Use secure enclaves or TPM chips to protect device-bound keys.

4. Enforce Strong Identity Hygiene

• Disable unused accounts and implement automated account lifecycle management.
• Apply adaptive authentication that adjusts trust based on device posture, location, and behavior.
• For admins and developers, enforce stricter controls: isolated environments, MFA with physical tokens, and no session persistence.

5. Educate Employees Against MFA Bypass Tactics

• Train teams to recognize and report MFA fatigue, push bombing, or unexpected verification requests.
• Encourage secure password management for any non-passwordless accounts (e.g., through enterprise vaults like 1Password or Bitwarden).

Organizational Recommendations

• Audit all login systems for password reuse and SSO misconfigurations — a critical step in strengthening overall cybersecurity posture.
• Create a response plan for credential leaks (internal and external) to reduce both operational and cybersecurity risks.
• Enable passwordless login only where risk-based context is validated, ensuring both convenience and cybersecurity resilience.
• Integrate identity telemetry into SIEM/XDR for better detection, forensics, and proactive cybersecurity monitoring.
• Identity is now the perimeter — and the weakest point in many organizations remains how users log in. That makes identity a central pillar of any effective cybersecurity strategy.
• Credential attacks aren’t going away — they’re adapting. And while passwordless systems are a powerful step forward, no authentication method is secure without proper implementation, context validation, and session control. Without these measures, organizations expose themselves to unnecessary cybersecurity gaps.

In 2025, the organizations that succeed won’t just replace passwords — they’ll build adaptive identity ecosystems that evolve as fast as attackers do, aligned with broader cybersecurity strategies.

At Fyld, we help clients:

• Assess their identity exposure risk
• Design and deploy secure passwordless strategies
• Detect and respond to credential stuffing attempts
• Harden federated identity systems and session infrastructure

Prepare for What’s Next — With Cyber Resilience by Design

Cybersecurity in 2025 is no longer just about defending networks — it’s about defending decision-making, automation, identity, and integrity.

As attackers continue to leverage AI, automation, and social engineering at scale, it’s clear that traditional cybersecurity defenses are no longer enough. Organizations must shift from a reactive to a proactive mindset — building cybersecurity resilience into every layer of infrastructure, from code and cloud to endpoints and employees.

At Fyld, we believe that the organizations that thrive will be the ones that:

• Treat cybersecurity as a business enabler, not a technical silo
• Secure the full lifecycle of digital operations — including vendors, data, and AI
• Build adaptive defenses that evolve as fast as the threats they face
• Empower teams with security awareness, not just technology

Our job is to help you understand the risks, prepare for impact, and lead your organization with confidence — no matter what’s coming next.