Cyber Resilience

CVE-2021-29486

HighPublic PoCDDoS

Published: 30 April 2021

Published
30 April 2021
Modified
21 November 2024
KEV Added
Patch
CVSS Score v3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.0066 71.6th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2021-29486 is a high-severity Improper Input Validation (CWE-20) vulnerability in Cumulative-Distribution-Function Project Cumulative-Distribution-Function. Its CVSS base score is 7.5 (High).

Operationally, ranked in the top 28.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

EU & UK References

Vulnerability details

cumulative-distribution-function is an open source npm library used which calculates statistical cumulative distribution function from data array of x values. In versions prior to 2.0.0 apps using this library on improper data may crash or go into an infinite-loop. In…

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the case of a nodejs server-app using this library to act on invalid non-numeric data, the nodejs server may crash. This may affect other users of this server and/or require the server to be rebooted for proper operation. In the case of a browser app using this library to act on invalid non-numeric data, that browser may crash or lock up. A flaw enabling an infinite-loop was discovered in the code for evaluating the cumulative-distribution-function of input data. Although the documentation explains that numeric data is required, some users may confuse an array of strings like ["1","2","3","4","5"] for numeric data [1,2,3,4,5] when it is in fact string data. An infinite loop is possible when the cumulative-distribution-function is evaluated for a given point when the input data is string data rather than type `number`. This vulnerability enables an infinite-cpu-loop denial-of-service-attack on any app using npm:cumulative-distribution-function v1.0.3 or earlier if the attacker can supply malformed data to the library. The vulnerability could also manifest if a data source to be analyzed changes data type from Arrays of number (proper) to Arrays of string (invalid, but undetected by earlier version of the library). Users should upgrade to at least v2.0.0, or the latest version. Tests for several types of invalid data have been created, and version 2.0.0 has been tested to reject this invalid data by throwing a `TypeError()` instead of processing it. Developers using this library may wish to adjust their app's code slightly to better tolerate or handle this TypeError. Apps performing proper numeric data validation before sending data to this library should be mostly unaffected by this patch. The vulnerability can be mitigated in older versions by ensuring that only finite numeric data of type `Array[number]` or `number` is passed to `cumulative-distribution-function` and its `f(x)` function, respectively.

CWE(s)

Related Threats

No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.

Affected Assets

cumulative-distribution-function project
cumulative-distribution-function
≤ 2.0.0

Mitigating Controls

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

addresses: CWE-835

Enables transfer to alternate site if an infinite loop at the primary renders processing unavailable.

addresses: CWE-20

Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.

addresses: CWE-20

Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.

addresses: CWE-835

Detects and mitigates infinite loops that produce sustained resource consumption.

addresses: CWE-20

Directly implements checks on information inputs to reject invalid data before processing.

addresses: CWE-20

Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.

References