CVE-2026-119197 in pyasn1
Summary
by MITRE • 10/29/2026
pyasn1 is a generic ASN.1 library for Python. Prior to 0.6.5, binary REAL decoding builds a large mantissa one octet at a time by shifting a growing integer and slicing the remaining byte string. Attacker-controlled ASN.1 includes a binary-encoded REAL with a large mantissa and reaches BER, CER, or DER decode(), with or without a schema containing REAL. RealPayloadDecoder.valueDecoder repeatedly performs a left shift, OR, and suffix copy for every mantissa octet, making decode time quadratic in mantissa length. A comparatively small REAL value can hold a decoding worker on one CPU core for seconds or longer and cause availability loss. This issue is fixed in version 0.6.5.
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Analysis
by VulDB Data Team • 10/29/2026
The pyasn1 library serves as a generic ASN.1 implementation for the Python programming language, widely utilized in network protocols such as SNMP, LDAP, and X.25 to encode structured data. A critical vulnerability exists within the binary REAL decoding logic of versions prior to 0.6.5, specifically affecting how large mantissas are processed during BER, CER, or DER parsing operations. This flaw represents a significant availability risk due to its potential for causing denial-of-service conditions through computational exhaustion rather than memory corruption or code execution.
The technical root cause lies in the implementation of the RealPayloadDecoder.valueDecoder function. When decoding binary-encoded REAL values with large mantissas, the library constructs the resulting integer by iterating through each octet of the mantissa sequentially. For every octet processed, the decoder performs a left shift on an increasingly large integer object and then applies a bitwise OR operation to incorporate the new bits. Crucially, this process is accompanied by slicing operations that copy suffixes of the byte string. Because Python integers are arbitrary-precision objects, their size grows linearly with each added octet. Consequently, the computational cost of shifting and copying these large integer representations increases proportionally with the current size of the number being built.
This algorithmic structure results in a quadratic time complexity relative to the length of the mantissa. In practical terms, this means that doubling the input size does not merely double the processing time but squares it. An attacker can exploit this by crafting malicious ASN.1 data containing a binary REAL with an artificially large mantissa. When such malformed or specially crafted input is passed to the decode() method, whether within a schema context or without one, the decoder enters a prolonged computation loop. The vulnerability allows a comparatively small payload to consume significant CPU resources for seconds or even longer on a single core, effectively hanging the processing thread and preventing it from handling other requests.
The operational impact of this flaw is primarily centered on service availability. Systems relying on pyasn1 for parsing network traffic or configuration files can experience severe performance degradation when exposed to crafted inputs. In high-throughput environments such as API gateways, monitoring systems using SNMP traps, or directory services processing LDAP queries, a single malicious packet could stall the worker process responsible for decoding that specific message. This creates an easy vector for denial-of-service attacks where minimal effort from the attacker results in substantial resource exhaustion and service unavailability for legitimate users.
This vulnerability is classified under CWE-400, which covers Uncontrolled Resource Consumption, as it allows an external actor to exhaust system resources through inefficient algorithmic handling of input data. From a threat intelligence perspective, this aligns with MITRE ATT&CK technique T1496, Resource Hijacking, specifically within the context of computational exhaustion used to disrupt service availability rather than for cryptomining or other malicious payloads. The attack does not require authentication in many scenarios where ASN.1 parsing is performed on incoming network data, making it particularly dangerous in exposed services.
The issue has been resolved in pyasn1 version 0.6.5 through optimizations that mitigate the quadratic complexity of the decoding process. Developers and system administrators should immediately upgrade to this patched version or later to eliminate the risk. For environments where upgrading is not immediately feasible, mitigation strategies include implementing strict input validation at network boundaries to reject ASN.1 structures with excessively large mantissas before they reach the pyasn1 parser. Additionally, deploying rate limiting on services that consume ASN.1 data can help mitigate the impact of such attacks by restricting the volume of requests a single source can process within a given timeframe.