CVE-2023-21608
Adobe Acrobat and Reader Use-After-Free Vulnerability
Executive Summary
CVE-2023-21608 is a critical severity vulnerability affecting appsec. It is classified as an undisclosed flaw. This vulnerability is actively being exploited in the wild.
Precogs AI Insight
"The primary vulnerability vector is rooted in within Adobe Acrobat and Reader, allowing the insecure processing of malicious payloads. Exploitation typically involves an attacker attempting to silently exfiltrate sensitive routing topologies and internal schemas. The Precogs AI's Code Property Graph analysis traces untrusted input to neutralize the threat at the source level."
What is this vulnerability?
CVE-2023-21608 is categorized as a critical Buffer Overflow flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
Adobe Acrobat and Reader contains a use-after-free vulnerability that allows for code execution in the context of the current user..
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
| Metric | Value |
|---|---|
| CVSS Base Score | 9.8 (CRITICAL) |
| Vector String | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H |
| Published | October 10, 2023 |
| Last Modified | October 10, 2023 |
| Related CWEs | N/A |
Impact on Systems
✅ Remote Code Execution: Attackers can overwrite the instruction pointer (EIP/RIP) to redirect execution to malicious shellcode.
✅ Memory Corruption: Overwriting adjacent memory regions can corrupt critical application state, leading to unpredictable privilege escalation.
✅ Denial of Service: Triggering segmentation faults and kernel panics results in immediate disruption of critical systems.
How to fix this issue?
Implement the following strategic mitigations immediately to eliminate the attack surface.
1. Memory-Safe Languages Where possible, migrate critical parsing logic to memory-safe languages like Rust or Go.
2. Safe Standard Libraries Replace unbounded C functions (strcpy, sprintf) with boundary-checking equivalents (strncpy, snprintf).
3. Compiler Defenses Ensure software is compiled with modern defensive flags: ASLR, DEP/NX, Stack Canaries (SSP), and Position Independent Executables (PIE).
Vulnerability Signature
// Vulnerable C Function
void parse_network_packet(char *untrusted_data) \{
char local_buffer[128];
// VULNERABLE: strcpy does not verify the length of the source data
strcpy(local_buffer, untrusted_data);
printf("Packet Processed.");
\}
// EXPLOIT PAYLOAD: 128 bytes of padding + [Overwrite EIP Address]
References and Sources
Vulnerability Code Signature
Attack Data Flow
| Stage | Detail |
|---|---|
| Source | Untrusted User Input |
| Vector | Input flows through the application logic without sanitization |
| Sink | Execution or Rendering Sink |
| Impact | Application 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