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AgentGuard
Python SAST with AI false positive reduction & auto-fix
34 built-in rules + Bandit's 100+ engine. Multi-agent LLM filter reduces false positives by up to 91% (validated by 15 peer-reviewed papers). Pipeline: scan → confirm → review → auto-fix in one command. Safe auto-fix with self-validation on 10/17 rule types. 100% local — code never leaves your machine. Zero telemetry. Free tier + Pro at $29/mo. PH Launch: $149/year with code PH2025.
I got tired of SAST tools flooding me with false positives and leaving me to fix everything by hand. So I built AgentGuard Pro.
The key difference: a multi-agent LLM filter that reviews every finding with code context — not just pattern matching. 15 peer-reviewed papers back the architecture. Our Confirm Agent alone cuts false positives by 91%.
It runs 100% locally. Your code never touches a cloud API.
Python-only for now. If this resonates, I'll add JS/TS next. What language would you want?
About AgentGuard on Product Hunt
“Python SAST with AI false positive reduction & auto-fix”
AgentGuard was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #142 on the daily leaderboard. 34 built-in rules + Bandit's 100+ engine. Multi-agent LLM filter reduces false positives by up to 91% (validated by 15 peer-reviewed papers). Pipeline: scan → confirm → review → auto-fix in one command. Safe auto-fix with self-validation on 10/17 rule types. 100% local — code never leaves your machine. Zero telemetry. Free tier + Pro at $29/mo. PH Launch: $149/year with code PH2025.
On the analytics side, AgentGuard competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how AgentGuard performed against the three products that launched closest to it on the same day.
Who hunted AgentGuard?
AgentGuard was hunted by lijin. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of AgentGuard including community comment highlights and product details, visit the product overview.
lijin