Lenny Omega Prime
Autonomous AI pentest platform with 134 attack modules
15 followers
Autonomous AI pentest platform with 134 attack modules
15 followers
Lenny is an AI-powered penetration testing platform that automates what takes security teams weeks. 134 attack modules (WordPress, AWS, Kubernetes, Active Directory...) Natural language interface - just say "scan that server" or "find vulns" 22-phase "Omega Strike" autonomous assault Professional compliance reports (PCI-DSS, HIPAA, SOC2) Multi-cloud support (AWS, Azure) One-time $1,499. No subscriptions. Full source code. Built by offensive security pros who got tired of juggling 50 tools.
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Launch Team / Built With
@roy_barbosa Hey, congrats on your launch! Quick heads-up, I was clicking around your page and couldn’t find the Terms of Service or Privacy Policy. You might already have them somewhere, but wanted to flag it in case they’re missing or not linked yet. Those usually get checked pretty early. Happy to help if useful :D
@natalija_kerstein Thank you for flagging this, super helpful. You’re right: the Terms of Service and Privacy Policy weren’t linked clearly. I just added them to the footer on the main page (and the affiliate page as well). Appreciate you taking the time to click around and point it out!
@roy_barbosa that's great! Of course, best of luck!
@Lenny Omega Prime What does Lenny find that traditional automated scanners usually miss?
@hellofriend956 Traditional scanners report raw output and stop. Lenny goes further: he correlates findings across recon, enumeration, and exploitation phases, highlighting chained vulnerabilites and context-specific misconfigurations scanners often miss.
What's different is that Lenny filters noise and flags only what actually matters, so pentesters spend time making decisions, not chasing false positives.
I'd love to hear from other security pros, what gaps do you see scanners missing in your workflow?
How do you prevent hallucinated findings or unsafe actions during a pentest?
@ginnjuice210 Great question. Lenny is designed to never act autonomously outside the defined scope. Every finding is tied to obsrvable evidence from recon and enumeration, and unsafe actions are explicitly blocked.
Hallucinated findings are minimized by cross-verifying results across multiple sources and scoring confidence levels. Anything flagged as low-confidence is clearly labeled, so human pentesters can make the final decision.
Curious how other security pros handle balancing automation with accuracy in their workflow?
Congrat on the launch. How does Lenny handle context and validation across findings to avoid false positives you usually get from automated scanners?
@dcforme12 Thanks! Great question. Lenny doesn't treat findings as isolated signals. He maintains session level context across recon, enumeration, and interactions, so results are evaluated in relation to the target's behavior rather than matched blindly to signatures.
Validation is evidence-driven: findings are cross-checked, confidence-scored, and anything that can't be substantiated is clearly marked instead of promoted as vulnerability. The goal is fewer false positives and more time spent on issues that actually matter.
Curious how others here usually validate scanner findings today.
Where does Lenny still struggle today compared to an experienced human pentester?
@rysmith1313 Great question. Lenny is excellent at handling large volumes of data and catching contextual findings that traditional scanners often miss. That said, it still relies on human intuition for complex logic flaws, social engineering tests, and interpreting ambiguous results. Think of Lenny as a productivity multiplier, it frees human pentesters to focus on high-impact analysis rather than replacing their expertise.
Curious if others have similar gaps with their current tools, or have found ways to complement AI in their workflows?
@Lenny Omega Prime @roy_barbosa What does Lenny's output actually look like at the end of an assessment? More like scanner results or a pentester's notes?
@pfrank85 Great question! Lenny’s output is a hybrid, it combines the structured, actionable format of professional pentester notes with the thoroughness of automated scanner results. Each finding includes context, confidence scores, and suggested next steps, so testers can immediately prioritize critical issues without wading through noise.
Curious if others have experienced challenges balancing scanner output and manual notes, how do you usually handle that in your workflows?
@roy_barbosa I usually end up exporting scanner results and then rewriting or restructuring them manually so they make sense to clients. The raw output is rarely client-ready. Anything that gets closer to “notes I’d actually hand over” instead of a vulnerability dump is a big win.
@pfrank85 That’s exactly the problem Lenny is built around. Most tools are great at finding issues but terrible at expressing them in a way clients actually understand. Lenny’s output is intentionally closer to deliverable‑ready notes: scoped impact, confidence, and remediation context, not raw dumps. The goal is to reduce the rewrite step so reports reflect analyst judgment, not scanner verbosity.
How steep is the learning curve for someone already doing pentests professionally?
@idlf69 Great question! Lenny was designed to slot directly into existing pentest workflows. For someone already doing professional pentests, the learning curve is minimal, the interface is intuitive and most users can start generating actionable findings within the first session. Lenny’s goal is to reduce time spent on repetitive tasks so experienced pentesters can focus on the most critical vulnerabilities.
Curious if others have tried integrating new AI tools into their workflows, and what challenges they faced?
@roy_barbosa That’s reassuring to hear! I like that it integrates with existing workflows instead of forcing a completely new process. Curious to see how it handles complex correlations in real-world assessments.