[Precogs AI] Auto-Fix: Cumulative vulnerabilities resolution

[sameer6pre]

Precogs Auto-Fix — 12 Vulnerabilities Fixed

3 files modified, 12 vulnerabilities fixed

Vulnerability Details

• File Path: sample-vuln/sam.py
• Vulnerability Type: SQL Injection
• Risk Level: Critical
  Explanation:
  The code constructs an SQL query by interpolating the 'username' directly into the SQL string using an f-string. An attacker-controlled username can inject SQL code (e.g., injecting OR logic or terminating the string) that will be interpreted by SQLite, enabling data exfiltration, modification, or other SQL-based attacks. There is no input validation or parameterization.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/app.py
• Vulnerability Type: SQL Injection
• Risk Level: High
  Explanation:
  The function constructs an SQL query by interpolating the 'username' parameter directly into the SQL statement. If 'username' contains crafted characters (quotes, SQL operators), an attacker can manipulate the SQL statement and perform SQL injection to read, modify or delete data.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/app.py
• Vulnerability Type: Command Injection
• Risk Level: High
  Explanation:
  The ping() route interpolates the 'ip' query parameter directly into a shell command string and passes it to os.system, which invokes a shell. An attacker can inject additional shell commands by including metacharacters (e.g., ;, &&) in the 'ip' parameter, leading to arbitrary command execution on the server.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/app.py
• Vulnerability Type: Insecure Deserialization (Pickle RCE)
• Risk Level: Critical
  Explanation:
  pickle.loads can execute arbitrary code embedded in a pickle stream. Passing attacker-controlled data (hex-encoded) into pickle.loads allows remote code execution on the server. This is a very high-risk vulnerability since pickle supports building arbitrary objects and calling functions during unpickling.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/app.py
• Vulnerability Type: Unsafe YAML Deserialization
• Risk Level: High
  Explanation:
  yaml.load with Loader=yaml.Loader can construct arbitrary Python objects and even invoke functions. If an attacker controls the input YAML, they can cause remote code execution or create sensitive objects. The safe alternative is yaml.safe_load which only constructs simple Python objects.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/test.py
• Vulnerability Type: Hard-coded Secret
• Risk Level: High
  Explanation:
  Primary: Hard-coded Secret (CWE-798) — A secret (SECRET_KEY) is hard-coded in source. Hard-coded credentials or secrets in code can be leaked via source control, logs, or attackers gaining read access to the repository, allowing token forging, impersonation, or decryption of sensitive data.

Also found: Weak Hashing Algorithm (CWE-327) — MD5 is a fast and cryptographically broken hash function unsuitable for password hashing. Passwords hashed with MD5 are vulnerable to brute-force and rainbow-table attacks. Secure password storage requires a slow, memory-hard algorithm (bcrypt, scrypt, Argon2) or PBKDF2 with appropriate iterations and per-password salt.
Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/test.py
• Vulnerability Type: Command Injection
• Risk Level: Critical
  Explanation:
  User-controlled input is concatenated into a shell command string and executed, enabling command injection. An attacker can inject shell control operators or command substitution to run arbitrary commands on the host.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/test.py
• Vulnerability Type: Insecure Deserialization
• Risk Level: Critical
  Explanation:
  pickle.loads allows execution of arbitrary code when deserializing untrusted input (it can instantiate arbitrary objects and call their constructors). Loading attacker-controlled pickles leads to remote code execution. Use safe formats (JSON) or whitelisting approaches for deserialization.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/test.py
• Vulnerability Type: Path Traversal
• Risk Level: High
  Explanation:
  The code opens a filename supplied by the user without validating or restricting it. Attackers can use path traversal (e.g., '../../etc/passwd') to read arbitrary files on the filesystem.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/test.py
• Vulnerability Type: Unsafe YAML Deserialization
• Risk Level: Critical
  Explanation:
  yaml.load with an unsafe loader can construct arbitrary Python objects and can result in code execution when parsing untrusted YAML. Use yaml.safe_load to restrict to simple, safe Python objects (mappings, lists, strings, numbers).
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/test.py
• Vulnerability Type: Server-Side Request Forgery (SSRF)
• Risk Level: High
  Explanation:
  Making HTTP requests to user-supplied URLs enables SSRF. An attacker can cause the server to make requests to internal-only services (e.g., metadata endpoints) or arbitrary hosts. Without validation, private IPs and loopback addresses may be accessed.
  Please review and address the issue accordingly.

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Vulnerability Details

• File Path: sample-vuln/test.py
• Vulnerability Type: Arbitrary Code Execution via eval
• Risk Level: Critical
  Explanation:
  eval executes arbitrary Python code provided in the expression string. If expression contains attacker-controlled content, this leads to remote code execution. Use safe evaluators (ast.literal_eval) or a math expression parser that restricts operations.
  Please review and address the issue accordingly.

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This PR was auto-generated by Precogs AI. Review the changes and verify CI results before merging.