CVE-2020-8243

What is this vulnerability?

CVE-2020-8243 is categorized as a high Code Injection flaw with a CVSS base score of 7.2. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

A vulnerability in the Pulse Connect Secure < 9.1R8.2 admin web interface could allow an authenticated attacker to upload custom template to perform an arbitrary code execution.

This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.

Risk Assessment

Impact on Systems

✅ Data Exfiltration: Attackers can extract sensitive data from backend databases, configuration files, or internal services.

✅ Authentication Bypass: Exploiting this flaw may allow unauthorized access to protected resources and administrative interfaces.

✅ Lateral Movement: Once initial access is gained, attackers can pivot to internal systems and escalate privileges.

How to Fix and Mitigate CVE-2020-8243

1. Apply Vendor Patches Immediately: This vulnerability is listed in CISA's Known Exploited Vulnerabilities catalog. Apply updates per vendor instructions.
2. Verify Patch Deployment: Confirm all instances are updated using Precogs continuous monitoring.
3. Review Audit Logs: Investigate historical access logs for indicators of compromise related to this attack surface.
4. Implement Defense-in-Depth: Deploy WAF rules, network segmentation, and endpoint detection to limit blast radius.

Defending with Precogs AI

A vulnerability in the Pulse Connect Secure administrative interface allows an authenticated user to perform arbitrary code execution. Attackers exploit missing input validation in the web dashboard to inject shell commands. Precogs Application Security Module tracks administrative inputs mapped to execution sinks.

Use Precogs to continuously scan your codebase, binaries, APIs, and infrastructure for this vulnerability class and related attack patterns. Our AI-powered detection engine combines static analysis with threat intelligence to identify exploitable weaknesses before attackers do.

Start scanning with Precogs →

Vulnerability Code Signature

Attack Data Flow

Vulnerable Code Pattern

# ❌ VULNERABLE: Dynamic code evaluation
def process_data(user_input):
    # Taint sink: arbitrary code execution
    result = eval(user_input)
    return result

Secure Code Pattern

# ✅ SECURE: Safe parsing
import ast
def process_data(user_input):
    # Sanitized parsing: only evaluates literal structures
    result = ast.literal_eval(user_input)
    return result

How Precogs Detects This

Precogs AI Analysis Engine identifies unsafe dynamic code evaluation paths by tracking untrusted data into sinks like eval() and exec().\n