CVE-2009-1918
published 2009-07-29CVE-2009-1918: Microsoft Internet Explorer 5.01 SP4 and 6 SP1; Internet Explorer 6 for Windows XP SP2 and SP3 and Server 2003 SP2; and Internet Explorer 7 and 8 for Windows…
PriorityP354critical10CVSS 2.0
AVNACLAuNCCICAC
EPSS
43.32%
98.6th percentile
Microsoft Internet Explorer 5.01 SP4 and 6 SP1; Internet Explorer 6 for Windows XP SP2 and SP3 and Server 2003 SP2; and Internet Explorer 7 and 8 for Windows XP SP2 and SP3, Server 2003 SP2, Vista Gold, SP1, and SP2, and Server 2008 Gold and SP2 do not properly handle table operations, which allows remote attackers to execute arbitrary code via a crafted HTML document that triggers memory corruption by adding malformed elements to an empty DIV element, related to the getElementsByTagName method, aka "HTML Objects Memory Corruption Vulnerability."
Affected
4 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| microsoft | internet_explorer | — | — |
| microsoft | internet_explorer | — | — |
| microsoft | internet_explorer | — | — |
| microsoft | internet_explorer | — | — |
Detection & IOCsextracted from sources · hover to see the quote
- →CVE-2009-1918 is triggered by adding malformed elements to an empty DIV element via the getElementsByTagName method, resulting in memory corruption — monitor for crafted HTML documents exploiting table operations in IE 5.01/6/7/8 ↗
- ·Affected versions are Internet Explorer 5.01 SP4, 6 SP1, 6 for XP SP2/SP3 and Server 2003 SP2, and IE 7/8 for XP SP2/SP3, Server 2003 SP2, Vista Gold/SP1/SP2, and Server 2008 Gold/SP2 — detections should be scoped to these specific platform/version combinations ↗
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arXiv
URSID: Using formalism to Refine attack Scenarios for vulnerable Infrastructure Deployment
arxiv_fulltext·2023-03-30
URSID: Using formalism to Refine attack Scenarios for vulnerable Infrastructure Deployment
URSID: Using formalism to Refine attack Scenarios for vulnerable Infrastructure Deployment
Pierre-Victor Besson
CentraleSupélec, Inria, univ. Rennes, CNRS, IRISA
Rennes
France
[email protected]
Valerie Viet Triem Tong
CentraleSupélec, Inria, univ. Rennes, CNRS, IRISA
Rennes
France
[email protected]
Gilles Guette
univ. Rennes, CNRS, Inria, IRISA
Rennes
France
[email protected]
Guillaume Piolle
Thales
Rennes
France
[email protected]
Erwan Abgrall
CentraleSupélec, Inria
Rennes
France
[email protected]
Besson et al.
## Abstract
In this paper we propose a novel way of deploying vulnerable architectures for defense and research purposes, which aims to generate deception platforms based on the formal descript
arXiv
Stochastic Simulation Techniques for Inference and Sensitivity Analysis of Bayesian Attack Graphs
arxiv_fulltext·2021-03-18
Stochastic Simulation Techniques for Inference and Sensitivity Analysis of Bayesian Attack Graphs
Stochastic Simulation Techniques for Inference and Sensitivity Analysis of Bayesian Attack Graphs
Stochastic Simulation for Bayesian Attack Graphs
Isaac Matthews1,2
Sadegh Soudjani1
Aad van Moorsel1
I. Matthews et al.
School of Computing, Newcastle University, United Kingdom
[email protected]
## Abstract
A vulnerability scan combined with information about a computer network can be used to create an attack graph, a model of how the elements of a network could be used in an attack to reach specific states or goals in the network. These graphs can be understood probabilistically by turning them into Bayesian attack graphs, making it possible to quantitatively analyse the security of large networks. In the event of an attack, probabilities on the graph change depending on th
arXiv
Cyclic Bayesian Attack Graphs: A Systematic Computational Approach
arxiv_fulltext·2020-05-13
Cyclic Bayesian Attack Graphs: A Systematic Computational Approach
Cyclic Bayesian Attack Graphs: A Systematic
Computational Approach
Isaac Matthews
Newcastle University
Newcastle upon Tyne, U.K.
[email protected]
John Mace
Newcastle University
Newcastle upon Tyne, U.K.
Sadegh Soudjani
Newcastle University
Newcastle upon Tyne, U.K.
Aad van Moorsel
Newcastle University
Newcastle upon Tyne, U.K.
## Abstract
Attack graphs are commonly used to analyse the security of medium-sized to large networks. Based on a scan of the network and likelihood information of vulnerabilities, attack graphs can be transformed into Bayesian Attack Graphs (BAGs). These BAGs are used to evaluate how security controls affect a network and how changes in topology affect security.
A challenge with these automatically generated BAGs is that cycles arise naturally,
http://support.nortel.com/go/main.jsp?cscat=BLTNDETAIL&id=953693http://www.securityfocus.com/archive/1/505523/100/0/threadedhttp://www.securityfocus.com/bid/35826http://www.securitytracker.com/id?1022611http://www.us-cert.gov/cas/techalerts/TA09-195A.htmlhttp://www.vupen.com/english/advisories/2009/2033http://www.zerodayinitiative.com/advisories/ZDI-09-047https://docs.microsoft.com/en-us/security-updates/securitybulletins/2009/ms09-034https://oval.cisecurity.org/repository/search/definition/oval%3Aorg.mitre.oval%3Adef%3A5524http://support.nortel.com/go/main.jsp?cscat=BLTNDETAIL&id=953693http://www.securityfocus.com/archive/1/505523/100/0/threadedhttp://www.securityfocus.com/bid/35826http://www.securitytracker.com/id?1022611http://www.us-cert.gov/cas/techalerts/TA09-195A.htmlhttp://www.vupen.com/english/advisories/2009/2033http://www.zerodayinitiative.com/advisories/ZDI-09-047https://docs.microsoft.com/en-us/security-updates/securitybulletins/2009/ms09-034https://oval.cisecurity.org/repository/search/definition/oval%3Aorg.mitre.oval%3Adef%3A5524
2009-07-29
Published