CVE-2017-9785
NancyFX Dangermouse RCE via Deserialization CSRF Cookie
Description
Csrf.cs in NancyFX Nancy before 1.4.4 and 2.x before 2.0-dangermouse has Remote Code Execution via Deserialization of JSON data in a CSRF Cookie.
INFO
Published Date :
July 20, 2017, 12:29 p.m.
Last Modified :
Nov. 21, 2024, 3:36 a.m.
Source :
[email protected]
Remotely Exploitable :
Yes !
Impact Score :
5.9
Exploitability Score :
3.9
Public PoC/Exploit Available at Github
CVE-2017-9785 has a 2 public PoC/Exploit
available at Github.
Go to the Public Exploits
tab to see the list.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2017-9785
.
URL | Resource |
---|---|
https://github.com/NancyFx/Nancy/releases/tag/v1.4.4 | Release Notes Third Party Advisory |
https://github.com/NancyFx/Nancy/releases/tag/v1.4.4 | Release Notes Third Party Advisory |
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Joux-Lercier vulnerability in the ECDSA algorithm allows attackers to generate fake transactions using forged signatures, which poses a privacy risk and can lead to the leakage of protected information. This paper discusses in detail the mechanisms for exploiting this vulnerability, including flaws in the deserialization process
bitcoin bitcoin-transaction bitcoin-wallet bitcoinhack btc btchack btchunter private-key
Jupyter Notebook
Learn about the DeserializeSignature vulnerability in Bitcoin's ECDSA signature algorithm and its potential impact on the security of Bitcoin transactions. Discover how the vulnerability can be exploited and what steps are being taken to mitigate the risk. Stay informed on the latest developments in Bitcoin security.
ai bitcoin bitcoin-wallet chatgpt colab-notebook language-modeling openai pytorch
Jupyter Notebook
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2017-9785
vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2017-9785
vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
-
CVE Modified by af854a3a-2127-422b-91ae-364da2661108
Nov. 21, 2024
Action Type Old Value New Value Added Reference https://github.com/NancyFx/Nancy/releases/tag/v1.4.4 -
CVE Modified by [email protected]
May. 14, 2024
Action Type Old Value New Value -
Initial Analysis by [email protected]
Jul. 25, 2017
Action Type Old Value New Value Added CVSS V2 (AV:N/AC:L/Au:N/C:P/I:P/A:P) Added CVSS V3 AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H Changed Reference Type https://github.com/NancyFx/Nancy/releases/tag/v1.4.4 No Types Assigned https://github.com/NancyFx/Nancy/releases/tag/v1.4.4 Release Notes, Third Party Advisory Added CWE CWE-502 Added CPE Configuration OR *cpe:2.3:a:nancyfx:nancy:1.4.3:*:*:*:*:*:*:* (and previous) *cpe:2.3:a:nancyfx:nancy:2.0.0:alpha:*:*:*:*:*:* *cpe:2.3:a:nancyfx:nancy:2.0.0:barneyrubble:*:*:*:*:*:* *cpe:2.3:a:nancyfx:nancy:2.0.0:clinteastwood:*:*:*:*:*:*
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2017-9785
is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2017-9785
weaknesses.
Exploit Prediction
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days.
0.50 }} -0.21%
score
0.76419
percentile