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Scan your AI agents for dangerous capabilities

Details

External ID
48804182
Source
HN
Company
—
Product
Scan your AI agents for dangerous capabilities
Website domain
github.com
Launched
July 6, 2026
Cohort
—
Upvotes
44
Upvotes percentile
0.8321385902031063
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Enrichment

Theme
ai cybersecurity and penetration testing
Vertical
Security
Function
Observability & eval
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
security scanner for ai agents
Manually corrected
False

Could you build this?

Partial The scanner runner and test framework are basic CRUD/CLI tasks, but creating reliable benchmark suites and red-teaming evaluations for dangerous model capabilities requires specialized safety research.

What it would actually take: Involves building an evaluation harness that subjects AI agent APIs to multi-turn adversarial red-teaming scenarios (e.g., prompt injection, SSRF, unauthorized tool execution, data exfiltration). The hard part is constructing comprehensive, high-fidelity security benchmarks that accurately evaluate capability boundaries rather than superficial keyword matching. Requires AI safety and prompt security domain expertise.

Discussion

19 comments analyzed.

Competitors mentioned: DashClaw, SELinux, AppArmor, Tomoyo, mitmproxy, gvisor, chroot jail

Concerns raised: OS-level controls insufficient for application/business logic constraints, Works better for host security than governing AI agent behavior, Scanner alone insufficient without runtime enforcement, Limited exposure in serverless/sandboxed container environments

Feature requests: Parameter-aware rules to block unsafe operations (e.g., trades over $1M), Contextual access control inspection before tool calls, not just RBAC, Multi-party and role-based access control modeling, Web traffic parsing for remote API calls to determine safety

Competitors

Other products that read as similar to this one — 1560 launches clear the similarity bar, closest 8 shown.

Attention rank: #220 of 1561 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 250 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a observability & eval tool for Media & entertainment yet.