Resources
A public hub of methodologies, advisories, benchmarks, and playbooks—built to help security and AI teams deploy LLM systems safely.
For educational purposes only; not legal advice.
Flagship pieces that reflect how we test and harden LLM applications in real environments.
A practical taxonomy of injection families and tool-call escalation paths, plus mitigations that hold under pressure.
Defensive design patterns that reduce retrieval manipulation and data exposure—without killing product utility.
Signals that matter, how to avoid noisy telemetry, and how to produce evidence SOC teams can actually use.
Structured write-ups with reproducible patterns, impact framing, and practical mitigations.
A pattern family where malicious prompt content influences tool arguments and downstream actions.
How poisoning survives summarization and truncation—and what controls actually reduce blast radius.
Practical documents you can apply during design reviews, incident response, and ongoing assurance.
A minimal, high-signal triage checklist for policy bypass attempts, drift, and unsafe tool usage.
How to design guardrails that hold up under ambiguity, social engineering, and long context.
A practical checklist for retrieval integrity, context bounding, source provenance, and redaction.
If you want DacShield to evaluate your specific use cases (agent tools, RAG, sensitive data paths), email us with your architecture and risk priorities.
