CVE-2021-35247

Improper Input Validation in Serv-U web login screen to LDAP authentication was allowing characters that were not sufficiently sanitized

Verified by Precogs Threat Research
Last Updated: Oct 27, 2025
Base Score
4.3MEDIUM

Executive Summary

CVE-2021-35247 is a medium severity vulnerability affecting appsec. It is classified as CWE-20. This vulnerability is actively being exploited in the wild.

Precogs AI Insight

"The Serv-U web login screen fails to sanitize input characters prior to LDAP authentication. Threat actors inject crafted LDAP queries to bypass authentication and extract directory information. Precogs Application Security Module identifies missing sanitization on LDAP query parameters."

Exploit Probability (EPSS)
Moderate (5.3%)
Public POC
Available
Exploit Probability
Low (<10%)
Public POC
Actively Exploited
Affected Assets
appsecCWE-20

What is this vulnerability?

CVE-2021-35247 is categorized as a medium Improper Input Validation flaw with a CVSS base score of 4.3. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

Serv-U web login screen to LDAP authentication was allowing characters that were not sufficiently sanitized. SolarWinds has updated the input mechanism to perform additional validation and sanitization. Please Note: No downstream affect has been detected as the LDAP servers ignored improper characters. To insure proper input validation is completed in all environments. SolarWinds recommends scheduling an update to the latest version of Serv-U.

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

MetricValue
CVSS Base Score4.3 (MEDIUM)
Vector StringCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N
PublishedJanuary 10, 2022
Last ModifiedOctober 27, 2025
Related CWEsCWE-20

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-2021-35247

  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

The Serv-U web login screen fails to sanitize input characters prior to LDAP authentication. Threat actors inject crafted LDAP queries to bypass authentication and extract directory information. Precogs Application Security Module identifies missing sanitization on LDAP query parameters.

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

StageDetail
SourceUntrusted User Input
VectorInput flows through the application logic without sanitization
SinkExecution or Rendering Sink
ImpactApplication compromise, Logic Bypass, Data Exfiltration

Vulnerable Code Pattern

# ❌ VULNERABLE: Unsanitized Input Flow
def process_request(request):
    user_input = request.GET.get('data')
    # Taint sink: processing untrusted data
    execute_logic(user_input)
    return {"status": "success"}

Secure Code Pattern

# ✅ SECURE: Input Validation & Sanitization
def process_request(request):
    user_input = request.GET.get('data')
    
    # Sanitized boundary check
    if not is_valid_format(user_input):
        raise ValueError("Invalid input format")
        
    sanitized_data = sanitize(user_input)
    execute_logic(sanitized_data)
    return {"status": "success"}

How Precogs Detects This

Precogs AI Analysis Engine maps untrusted input directly to execution sinks to catch complex application security vulnerabilities.\n

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Is your system affected?

Precogs AI detects CVE-2021-35247 in compiled binaries, LLMs, and application layers — even without source code access.