Content safety filter bypasses across multiple frontier AI models using prompt
reframing tactics: academic chemistry, forensic training scenarios, pharmaceutical
analysis, verbose simulation, patent litigation framing, and incremental escalation patterns.
Each variant bypasses model-level guardrails without triggering refusal heuristics.
ai-safetymultiple models0din.ai
Indirect Prompt Injection via Embedded Content
multiple submissions
Data exfiltration through indirect prompt injection in AI-powered applications that
process external content: email clients, document readers, and web browsing agents.
Injected instructions embedded in legitimate-looking content redirect agent behavior
to leak conversation context or user data.
prompt-injectionexfiltration0din.ai
Agentic Attack Surfaces in AI Coding Tools
multiple submissions
Attack chains targeting AI coding agents through workspace configuration files,
package manager lifecycle hooks, and git repository metadata. Includes
DNS-controlled payload delivery via npm postinstall, invisible Unicode injection
in commit messages, and AGENTS.md trust exploitation.