New Firefox flaws enable DoS attacks

By
Follow google news

Popular alternative web browser Mozilla Firefox contains a vulnerability that could allow an attacker to launch denial of service (DoS) attacks, security monitoring service Secunia said in an advisory today.

Although rated "not critical" by Secunia, the bug "can be exploited to corrupt the memory (of Firefox) and cause a crash." The execution of abnormal JavaScript causes the flaw.


The vulnerability has been confirmed in version 1.5.0.2, yet other versions may also be affected, Secunia said. As users await a patch, Secunia suggests disabling JavaScript when visiting unknown websites.

According to media reports, Firefox has developed a patch, but it has yet to be distributed to users.

News of the vulnerability came five days after Mozilla announced two "critical" flaws affecting Firefox.

One flaw is caused by the execution of JavaScript embedded in an email message, according to a company advisory. The code can increase client privileges and be used to install malware or send spam.

Mozilla suggested users switch to plain text when emailing as the flaw only affects HTML composition.

The other bug, discovered through TippingPoint's Zero Day Initiative, is caused by "an invalid and nonsensical ordering of table-related tags," which could allow the attacker to run malicious code, a second company advisory said. Users should update to a fixed version to avoid potential problems.

Add iTnews as your trusted source

Got a news tip for our journalists? Share it with us anonymously here.
Copyright © SC Magazine, US edition
Tags:

Most Read Articles

US medical device maker Stryker's Microsoft environment attacked

US medical device maker Stryker's Microsoft environment attacked

Poor WA gov M365 security led to $71k theft and children's data breached

Poor WA gov M365 security led to $71k theft and children's data breached

CBA chief impersonated in global investment fraud on Facebook

CBA chief impersonated in global investment fraud on Facebook

Services Australia describes fraud, debt-related machine learning use cases

Services Australia describes fraud, debt-related machine learning use cases

Log In

  |  Forgot your password?