Do AI assistants create new insider risk, and what limits it?
AI assistants add two insider paths: staff pasting sensitive data in, and assistants acting with a user's access. Limit data, permissions and autonomy.
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.
AI assistants add two insider paths: staff pasting sensitive data in, and assistants acting with a user's access. Limit data, permissions and autonomy.
AI assistants make it easy to paste, index and send data no one meant to share. Seven common mistakes and the controls OWASP and CISA guidance point to.
AI assistants inherit an employee's access and can leak or misuse it by accident or by instruction. Scope access, log actions, gate risky steps.
A review checklist for engineering leads on OWASP LLM05: what to ask your teams, which controls to require, and what evidence shows the work is done.
Scope the bot, test what it can reach and reveal, log every run and fix the permissions behind it. A defensive plan built on the OWASP LLM Top 10 list.
Sandboxes limit where an agent can act. Guardrails govern what it is allowed to do. Learn the difference, the gaps in each, and why you want both layers.
Free tools can scan dependencies, flag risky projects and run static checks on AI-written code, but each has limits. See what each category misses.
AI agents and robots on a food line add software paths to physical equipment. Here is how OT standards and OWASP guidance help you scope the new risks.
AI assistants speed up coding and can also suggest insecure or non-existent libraries. Frame it for finance as review cost, with three checks to fund.
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