Match an LLM's privileges to whoever wrote its input
A design rule for LLM security automation: when the model reads content from a party, give it no more power than that party has. Examples and trade-offs.
Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
A design rule for LLM security automation: when the model reads content from a party, give it no more power than that party has. Examples and trade-offs.
Credible but false output can cause breaches, legal exposure and bad code. What OWASP says about LLM misinformation and the controls that reduce it.
If you expose your own model through an API, limit logprobs, input size, rate and access. The OWASP controls against extraction, replication and abuse.
What access a coding agent actually needs, what to withhold, and how to scope files, shell, network and credentials so one bad instruction stays small.
What permissions an AI review bot or coding agent needs in CI, what to withhold, and how to check the token it runs with. A practical checklist.
Keras load_model has a safe_mode flag that blocks unsafe Lambda deserialization in v3 files. Here is what it covers and why you should leave it on.
Jailbreaking is a form of prompt injection aimed at removing safety rules. A short guide to choosing the right term in tickets, reports and audits.
The NIST AI RMF is voluntary and not a certification, but contracts, customers or other rules may still point to it. How closely should you follow it?
A second model that screens inputs and outputs is useful, but it can be injected too. Why guardrail models are one layer and what to pair them with.
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