AI Jailbreak

Cryptographers have demonstrated that AI safety filters designed to protect Large Language Models (LLMs) inherently possess vulnerabilities due to their computationally constrained nature compared to the models themselves. Researchers exemplified this through "controlled-release prompting" using substitution ciphers and theoretically with time-lock puzzles, allowing malicious prompts to bypass filters and extract forbidden information.

What Happened

Cryptographers have demonstrated that AI safety filters designed to protect Large Language Models (LLMs) inherently possess vulnerabilities due to their computationally constrained nature compared to the models themselves. Researchers exemplified this through "controlled-release prompting" using substitution ciphers and theoretically with time-lock puzzles, allowing malicious prompts to bypass filters and extract forbidden information.

Why This Matters

Current evidence identifies a security issue involving the affected technology, but does not yet support a more specific impact claim.

Recommended Action

No confirmed vendor remediation is available in the current evidence. Confirm whether the affected technology is present in your environment and review the affected configuration.

Exposure

Exposure reason: This incident does not currently match a technology in My AI Stack.

Exploitation status: UNKNOWN

Primary entities:

Timeline

• Incident first seen
  Dec 10, 2025 05:30

  BugSkan first recorded this incident.

• Cryptographers Show That AI Protections Will Always Have Holes - Quanta Magazine
  Dec 10, 2025 05:30

  quantamagazine.org · Research

Sources

My AI Stack Match