VulnerabilityPublished 31 Oct 2026

CVE-2026-119194: Awscli@1 · pyasn1 has quadratic CPU use in schemaless BER/CER/DER container decoding

Affects awscli@1Source GCVE Database

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Authoritative record:CVE-2026-119194· High 7.5

Not known to be exploited · CVSS 7.5 High.

Data as of 31 Oct 2026, 16:23 UTC

CVSS 3.1 base score

7.5High

How severe the flaw is on the 0–10 CVSS scale.

Thin evidence

One scorer or none

CVSS scores by source
CNA (GitHub_M)	CVSS 3.1	7.5

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
User Interaction: None
Scope: Unchanged
Confidentiality: None
Integrity: None
Availability: High

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: None: There is no loss of confidentiality within the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: High: There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 29 Oct 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 30 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Affected software

Product	Affected	Fixed in
Homebrewawscli@1`pkg:brew/awscli%401`Other threats	Affected >=1.20.20	Fixed in–

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AI-suggested

Until a fix is available, avoid passing untrusted or attacker-controlled BER, CER, or DER data to schemaless decoding functions in pyasn1.

Description

CVE-2026-119194 is a high-severity vulnerability in pyasn1 used by awscli@1 (versions >=1.20.20) where schemaless decoding of BER, CER, or DER data with many distinct long tag IDs causes quadratic CPU usage. This can lead to excessive CPU consumption and reduced service availability when processing attacker-controlled inputs. No confidentiality or integrity impacts are reported.

Impact

The vulnerability allows an attacker to cause high CPU usage on applications that decode attacker-controlled BER, CER, or DER data without an ASN.1 schema, potentially leading to denial of service due to resource exhaustion. There is no impact on confidentiality or integrity, only availability.

Summary

The vulnerability arises from the ConstructedPayloadDecoderBase._decodeComponentsSchemaless method in pyasn1 v0.6.4, which inserts every decoded component's TagSet into a growing set to distinguish tag sets. Attacker-controlled tag IDs can cause hash collisions, resulting in each insertion requiring comparisons against an increasing number of earlier tags, leading to quadratic CPU time growth. This affects BER, CER, and DER schemaless decoding. The issue was demonstrated with a proof-of-concept showing CPU time increasing disproportionately with input size. The fix involves stopping growth of the classification set after two distinct tag sets are detected, preserving decoding correctness while preventing CPU exhaustion.

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 31 Oct 2026, 16:23 UTC

Technical details

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