A pentest on every deploy not every year
HACKBOTAn autonomous agent that attacks your live app like a human would reading the frontend, probing auth, then chaining small findings into the one that breaches. On every deploy. The annual PDF is obsolete.
scan_run · 6m 18s · 142 endpoints · 3 critical · 7 high
Frontend
Recon
BOLA
Server
Notes
Chain
Report
HackBot agent
$
frontend · parsed app bundle · 187 routes, 24 API hosts
09:14:02
$
recon · fuzzed /api/* · 142 reachable, 9 undocumented
09:14:31
$
bola · /api/users/:id returns peer records · CRIT
09:16:12
$
server · SSRF in image_proxy → 169.254.169.254 reachable · CRIT
09:18:47
$
notes · leaked admin_token in /api/users/42 body · lead saved
09:19:30
$
chain · bola → admin_token → SSRF → customer PII · verified
09:20:11
$
report · 1 critical chain, 3 standalone crits, 7 high · PR drafted
09:20:20
bola → token → ssrf → exfil
step 1 · bola
GET /api/users/41
step 2 · token
admin_token leaked
step 3 · ssrf+pivot
/exports.json → PII
step 1 · bola
GET /api/users/41
step 2 · token
admin_token leaked
step 3 · ssrf+pivot
/exports.json → PII
A traditional pentest is a snapshot of an app that no longer exists by the time the report lands. HackBot closes the gap by making offensive testing a build step continuous, autonomous, and tied to the exact change that introduced the risk.
A merge to main or a deploy webhook kicks off HackBot automatically. New routes in the diff become new attack surface the same minute they go live.
The agent reasons through frontend analysis, recon, access-control probing, server-side testing, and lead-gathering adapting its next move to what the last one revealed.
The differentiator: HackBot composes low-severity findings into the multi-step exploit that actually reaches your data then verifies the chain end to end before reporting it.
Each finding ships with the request, the payload, the blast radius, and a suggested fix often as a drafted PR. It re-tests on the next deploy to confirm the fix held.
Vulnerability scanners list problems. HackBot reasons like an attacker: it gathers leads, connects them, and proves the path to impact so you fix the breach, not triage a thousand low-severity lines.
HackBot works like a skilled human tester each phase informs the next. It reads your frontend, finds the real (and undocumented) API surface, then probes the flaws scanners miss because they need reasoning, not signatures.
Frontend analysis to map the app as users and code see it
BOLA / IDOR and broken-auth testing across real object graphs
Server-side: SSRF, injection, and logic flaws, with lead-tracking
Every finding is reproducible and verified no "potential" or "informational" noise. You get the exact request, the data it reached, the controls it violated, and a suggested fix, often as a drafted PR.
Reproducible PoC: the literal request and payload
Blast radius: what data or system the exploit actually reached
Suggested fix as a PR; re-verified on the next deploy
HackBot runs on every deploy and tracks your attack surface over time. A new route ships today, it's tested today; a fix merged this morning is re-verified this afternoon a living view of exploitability, with the evidence trail to prove it.
Triggered by merge-to-main or a deploy webhook
Diff-aware: new and changed routes prioritized automatically
Each scan is signed evidence pentest coverage your auditor accepts
You define the scope, environments, and blast radius. HackBot respects rate limits, honors a destructive-action allowlist, and runs full-force on staging while staying read-only in prod with every action logged.
Per-environment aggression and destructive-action controls
Scoped to the hosts and routes you authorize nothing else
Full action log; HackBot's own activity is itself evidence
HackBot focuses on the vulnerability classes that scanners systematically miss the ones that depend on understanding your app's logic and chaining context together.
Accessing other users' objects by manipulating identifiers the #1 API risk, and invisible to signature scanners.
Server-side request forgery, injection, and deserialization the flaws that reach internal infrastructure.
Flaws in authentication, token handling, and session management that let an attacker become someone else.
Abuses of intended functionality the flaws no wordlist contains because they're unique to your app.
New attack surface introduced by a deploy undocumented endpoints, debug routes, and forgotten test handlers.
The whole point: composing the above into a verified, end-to-end path from a low-severity bug to real impact.
When we evaluated our options for compliance and securing our systems, we found that UprootSecurity's compliance and security model aligned perfectly with our needs. It gave our team real-time visibility into the end-to-end process, saving our engineers hundreds of hours of manual effort.
Autonomous offensive testing against a live app raises real questions. Here’s how HackBot stays safe and useful.
Yes, with guardrails. In production it runs read-only and rate-limited, with a destructive-action allowlist you control full-force on staging, conservative in prod. Every request is logged.
Scanners match signatures and produce long lists of mostly-low findings. HackBot reasons like an operator gathering leads across phases and chaining them into a verified, end-to-end exploit. It reports the breach path, not a thousand "informational" lines.
It replaces the repetitive coverage you’d otherwise get once a year, on every deploy. Many teams keep a periodic human engagement for deep, creative work and use HackBot to catch regressions between them it raises the floor continuously.
No findings are verified before reporting, deduplicated against open issues, and routed to the owning service with a reproducible PoC and a suggested fix. Your team sees confirmed breaches, not a triage queue.
Each scan is signed and filed in your evidence library with scope, findings, and remediation trail satisfying the periodic-pentest controls in SOC 2, ISO 27001, and PCI. Because it’s continuous, your coverage is never a year stale.
Authorize a scope, connect your deploy webhook, and get a verified findings report on the next release with the requests, the chain, and the fix.
On every deploy
Triggered by merge-to-main or a webhook.
Verified findings only
Reproducible PoC, no informational noise.
Real exploit chaining
Low-severity bugs composed into the actual breach.
Counts as evidence
Signed scans satisfy periodic-pentest controls.
