The 11 runtime attacks breaking AI security — and how CISOs are stopping them

Enterprise security teams are facing a new challenge as AI-enabled attacks gain ground. The threat model has shifted, with AI agents moving into production and attackers exploiting weaknesses at runtime. Breakout times are now measured in seconds, patch windows in hours, and traditional security measures are struggling to keep up.

According to CrowdStrike’s 2025 Global Threat Report, breakout times can be as fast as 51 seconds, with attackers moving quickly from initial access to lateral movement. What’s more, 79% of detections are now malware-free, as adversaries use hands-on keyboard techniques to bypass traditional endpoint defenses.

CISOs like Mike Riemer from Ivanti are witnessing a rapid collapse in the time between patch release and weaponization. Threat actors are now reverse engineering patches within 72 hours, leaving organizations vulnerable to exploits if they don’t patch quickly. The speed of attacks has been greatly enhanced by AI, making manual patching processes too slow to keep up.

Traditional security measures are failing to combat the new wave of AI-enabled attacks because they are semantic, not syntactic. SQL injections with recognizable signatures can be blocked with near-zero false positives, but attacks that ignore previous instructions are much harder to detect. Gartner’s research warns that businesses will embrace generative AI regardless of security risks, with shadow AI becoming a certainty.

To address the 11 attack vectors that bypass traditional security controls, security leaders and AI builders must implement new defensive strategies. These include intent classification to recognize jailbreak patterns, context-aware analysis to catch camouflage attacks, and stateful context tracking to detect multi-turn crescendo attacks. Defense-in-depth strategies based on deterministic rules are no longer sufficient against the semantic nature of these new attacks.

Gartner predicts that 25% of enterprise breaches will be traced to AI agent abuse by 2028, making it crucial for organizations to build defenses now. Deployment priorities include automating patch deployment, deploying normalization layers to decode malicious instructions, implementing stateful context tracking, enforcing RAG instruction hierarchy, and propagating identity into prompts for authorization context.

CISOs need to adopt a zero-trust approach to security, ensuring that communication is only allowed with verified entities. The consequences of failing to address these new threats can be severe, as seen in cases where Microsoft’s exposure went undetected for years and Samsung leaked code for weeks. It’s not a matter of if organizations should deploy inference security, but rather how quickly they can close the gap before becoming the next cautionary tale.