VulnerabilityPublished 13 Aug 2026Updated 31 Oct 2026

CVE-2026-59886: pyasn1 · Uncontrolled resource consumption when converting decoded REAL values

Affects gcalcliSource GCVE Database

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Not known to be exploited · CVSS 7.5 High : upgrade to 4.5.1_13 soon.

Data as of 1 Nov 2026, 01:38 UTC

CVSS 3.1 base score

7.5High

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

Patch: Available – fixed in 4.5.1_13

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 13 Aug 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 31 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

Upgrade gcalcli to 4.5.1_13.

Affected software

Product	Affected	Fixed in
Homebrewgcalcli`pkg:brew/gcalcli`Other threats	Affected >=4.3.0 <4.5.1_13	Fixed in 4.5.1_13

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

A fix is available in pyasn1 version 0.6.4 and later. Users should upgrade to this version or newer. As a workaround, avoid converting, printing, or comparing decoded Real objects from untrusted sources and instead inspect the raw (mantissa, base, exponent) tuple directly.

Description

A vulnerability in pyasn1's univ.Real type causes excessive CPU and memory consumption when converting decoded REAL values with very large exponents to Python floats. This can lead to denial of service if applications decode untrusted ASN.1 data and then convert, print, or compare these REAL values. The issue is fixed in pyasn1 version 0.6.4 and later.

Impact

Applications that decode untrusted ASN.1 REAL values and subsequently convert, print, or compare these values may experience denial of service due to excessive CPU and memory consumption. The vulnerability does not affect decoding alone but any operation triggering float conversion on the decoded Real objects. This can cause the process to hang, impacting availability.

Summary

The pyasn1 library's univ.Real type converts its (mantissa, base, exponent) tuple to a Python float using exact big-integer exponentiation. BER/CER/DER-encoded REAL values with large exponents cause the conversion to attempt materializing astronomically large integers, resulting in excessive CPU and memory usage. This affects float conversion operations such as prettyPrint(), str(), comparisons, arithmetic, and explicit float() calls. The vulnerability can be triggered by decoding untrusted ASN.1 data and then performing these operations on the decoded Real objects. The encoders and native codec are not affected. The issue is fixed in pyasn1 0.6.4 by using math.ldexp() for binary values and raising OverflowError for decimal values with out-of-range exponents without constructing large intermediate integers.

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What to do

Affected software

Description

AI analysisMachine-generated, updated 1 Nov 2026, 01:38 UTC

Technical details

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