Web Application Penetration Testing

A phased pentesting workflow for running web applications. Adapted from Shannon's pipeline (Keygraph, AGPL — concepts only, no code borrowed). Built around three rules:

1. No exploit, no report — every finding requires reproducible evidence.
2. Bounded scope — every active request goes against a target the operator pre-declared. Off-scope hosts are refused.
3. Bypass exhaustion before false-positive dismissal — a "blocked" payload is not a clean bill of health until you've tried the bypass set.

⚠️ Hard Guardrails — Read Before Every Engagement

Violating any of these invalidates the engagement and may be illegal.

1. Authorization gate. Before the first active scan in a session, you MUST confirm with the user, in writing, that they own or have written authorization to test the target. Record the acknowledgement in engagement/authorization.md (see template). No acknowledgement → no active scanning. Reading public pages with curl is fine; sending payloads is not.

2. Scope allowlist. Maintain engagement/scope.txt — one hostname or CIDR per line. Every nmap, curl, whatweb, browser navigation, or payload-bearing request MUST be against an entry in scope. If a target redirects you off-scope (3xx to a different host, a link in HTML), STOP and confirm with the user before following.

3. No production systems without paper. If the user hasn't told you "yes, prod is in scope and I have written sign-off," assume not. Default targets are staging, local docker, dedicated test instances.

4. Cloud metadata is off by default. Do not probe 169.254.169.254, metadata.google.internal, 100.100.100.200, [fd00:ec2::254], or equivalent unless the engagement explicitly includes SSRF-to-metadata as a goal AND the target is one you control. The agent's browser tool can reach these from inside your own infrastructure — don't.

5. Destructive payloads need approval. SQLi payloads that DROP/DELETE, filesystem-write SSTI, command injection with rm/shutdown/mkfs, anything that mutates beyond a single test row → ASK FIRST. The approval.py system catches some; don't rely on it alone.

6. Aux-client leakage risk (Hermes-specific). This skill produces sessions full of SQLi/XSS/RCE payloads, captured credentials, JWT tokens. Hermes' compression and title-generation paths replay history through the auxiliary client (often the main model). Anything sensitive you write to the conversation can leave the box on the next compress. Mitigation:

   • Redact captured tokens/credentials to the LAST 6 CHARS before logging them in any message. Full values go to engagement/evidence/ files, never into chat history.
   • If the engagement is sensitive, set auxiliary.title_generation.enabled: false in ~/.hermes/config.yaml for the session.

7. Rate limit yourself. Default 200ms between active requests against any single host. The recon-scan.sh script enforces this. Don't bypass it without operator approval.

8. Authority of the report. This skill produces a security assessment, not a "PASS." Even a clean run is "no exploitable issues FOUND in scope X within time T using methods Y" — not "the application is secure." Mirror that language in the report.

Phase 0: Engagement Setup

Before any scanning happens, create the engagement directory and authorization acknowledgement.

ENGAGEMENT=engagement-$(date +%Y%m%d-%H%M%S)
mkdir -p "$ENGAGEMENT"/{evidence,findings,reports}
cd "$ENGAGEMENT"

1. Ask the user (verbatim):

   "Confirm: (a) the target URL is [X], (b) you own this application or have written authorization to test it, and (c) the engagement may run for up to [N] hours starting now. Reply 'authorized' to proceed."

2. Wait for explicit authorized response. Any other answer means STOP.

3. Record authorization to engagement/authorization.md using the template in templates/authorization.md. Include:

   • Target URL(s) and IP(s)
   • Authorization basis (ownership / written authz from $name)
   • Engagement window
   • Out-of-scope items (production, third-party services, etc.)
   • Operator name (the user driving this session)

4. Build scope.txt:

   Copy

   localhost
   127.0.0.1
   staging.example.com
   192.168.1.0/24    # internal lab only, with operator OK
   

5. Read references/scope-enforcement.md before issuing the first active request — that doc has the host-extraction rules you apply to every command/URL before it goes out.

Phase 1: Pre-Recon (Code Analysis, optional)

Skip if no source access (black-box engagement).

If you have read access to the application source:

1. Map the architecture — framework, routing, middleware stack
2. Inventory sinks — every execute(, os.system(, eval(, template render, file read/write, redirect target
3. Map auth — session cookie vs JWT, OAuth flows, password reset, privileged endpoints
4. Identify trust boundaries — what's authenticated, what's not, what comes from request.*
5. Backward taint from each sink to a request source. Early-terminate when proper sanitization is found (parameterized queries, allowlists, shlex.quote, well-known escapers).

Output: evidence/pre-recon.md — architecture map, sink inventory, suspected vulnerable code paths.

This is OFFLINE work. No traffic to the target.

Phase 2: Recon (Live, Read-Only)

Maps the attack surface. All requests are GETs of public pages, no payloads yet. Still scope-bounded.

1. Verify scope. Resolve every target hostname → IP. Confirm IPs are in scope (avoids the "DNS points somewhere unexpected" trap).

2. Network surface (only if scope permits port scanning):

   bashCopy

   nmap -sT -T3 --top-ports 100 -oN evidence/nmap.txt $TARGET
   

   Use -T3 (default), not -T4/-T5. Stealthier and avoids tripping IDS/IPS in shared environments.

3. Tech fingerprint:

   bashCopy

   whatweb -v $TARGET_URL > evidence/whatweb.txt
   curl -sIk $TARGET_URL > evidence/headers.txt
   

4. Endpoint discovery:

   • Crawl the app with the browser tool (browser_navigate, browser_get_images, follow links).
   • Inspect robots.txt, sitemap.xml, .well-known/*.
   • Use the developer tools network panel via browser tool to capture XHR/fetch calls.

5. Auth surface: Identify login, registration, password reset, session cookie names, token formats. Do NOT send credentials yet — just observe.

6. Correlate with pre-recon (if you have source). For each evidence/pre-recon.md finding, mark whether the live surface confirms it's reachable.

Output: evidence/recon.md — endpoints, technologies, auth model, input vectors.

Phase 3: Vulnerability Analysis

One delegate_task per vulnerability class. Each agent reads evidence/recon.md (+ evidence/pre-recon.md if present), produces findings/<class>-queue.json using templates/exploitation-queue.json.

Use delegate_task with these focused subagents (parallel where possible):

Each queue entry has: id, vuln class, source (file:line if known), endpoint, parameter, slot type, suspected defense, verdict (identified / partial / confirmed / critical), witness payload, confidence (0-1), notes.

The analysis phase doesn't send malicious payloads yet — it stages them. The exploitation phase actually fires them.

Phase 4: Exploitation (Proof-Based, Conditional)

Only run a sub-agent per class where the analysis queue has actionable entries (identified or partial).

For each candidate:

1. Pre-send check — host in scope? auth gate satisfied? payload approved if destructive?
2. Send the witness payload — minimal proof. SQLi: ' AND 1=1-- then ' AND 1=2--. XSS: a benign marker like <svg/onload=console.log("HERMES-PENTEST-XSS")>. Never alert(1) in stored XSS — it'll fire for other users in shared environments.
3. Verify the witness fires — for blind injection, use a sleep probe (SLEEP(5)) and time the response. For SSRF, use a tester-controlled callback host you own (NOT a public service like webhook.site for sensitive engagements — exfil paths).
4. Promote level:
   • L1 Identified — pattern matched, no behavior change
   • L2 Partial — sink reached, but defense in place
   • L3 Confirmed — payload changed app behavior in observable way
   • L4 Critical — data extracted, code executed, access escalated
5. Bypass exhaustion before classifying as FP. For each candidate that blocks: try at least the bypass set in references/bypass-techniques.md for that class. Only after the set is exhausted may you write verdict: false_positive.
6. Record evidence for every L3/L4:
   • Full request (method, URL, headers, body)
   • Response (status, headers, relevant body excerpt)
   • Reproducer command (curl one-liner)
   • Impact statement

Output: findings/exploitation-evidence.md

Redact in evidence files:

• Any captured credentials/tokens → last 6 chars only in chat; full value to findings/secrets-vault.md (gitignored).
• Other users' PII → redact.
• Your test credentials → fine to keep.

Phase 5: Reporting

Generate the final report using templates/pentest-report.md. Sections:

1. Executive summary
2. Engagement scope (from engagement/scope.txt)
3. Authorization (from engagement/authorization.md)
4. Findings (L3/L4 only — proof-required). Per finding:
   • Title, severity (CVSS 3.1), CWE
   • Affected endpoint(s)
   • Proof (request + response excerpt)
   • Reproduction steps
   • Impact
   • Remediation
5. Not-exploited candidates (L1/L2 with notes on what blocked them)
6. Out-of-scope observations
7. Methodology / tools used
8. Limitations and what was NOT tested

Severity policy: CVSS only for L3/L4. L1/L2 are "candidates pending verification" — don't assign CVSS to unverified findings.

When to Stop

• The user revokes authorization.
• A candidate finding clearly impacts production data and you don't have approval for destructive testing — STOP and ask.
• The target starts returning 503/429 storms — back off, reconvene with the operator.
• You discover something outside the contracted scope (e.g. an exposed customer database while testing an unrelated endpoint). STOP, document, report to the operator. Do not pivot without explicit approval — that pivot is what makes pentesting illegal.

What This Skill Does NOT Cover

• Network-layer pentesting beyond port scanning (no Metasploit, Cobalt Strike, AD attacks, network protocol fuzzing).
• Reverse engineering / binary analysis (see issue #383).
• Source-only static analysis (see issue #382).
• Active social engineering / phishing.
• Anything against systems the operator hasn't pre-authorized.

If the engagement needs any of these, escalate to a professional pentester. This skill complements professional pentesting; it does not replace it.

Further Reading

• references/scope-enforcement.md — how to bound every active request
• references/vuln-taxonomy.md — slot types, render contexts, OWASP map
• references/exploitation-techniques.md — per-class payload patterns
• references/bypass-techniques.md — common WAF/filter bypasses
• templates/authorization.md — engagement authorization template
• templates/pentest-report.md — final report template
• templates/exploitation-queue.json — per-class finding queue schema
• scripts/recon-scan.sh — rate-limited nmap+whatweb+headers wrapper