UI Redressing Mayhem: Identification Attacks and UI Redressing on Google Chrome

Today I'm going to disclose a series of UI Redressing issues that could be exploited in order to extract information that may help an attacker to identify a victim-user whenever anonymity is a critical requirement. Moreover, a new extraction method, which has been successfully applied against Google Chrome, will be presented. Google's web browser disallows cross-origin drag&drop and what I'm introducing here is a completely different approach to achieve the extraction of potentially sensitive data.

Identification Attacks

I found that several world-renowned web applications lack protection of web resources from UI Redressing attacks, thus revealing data that can be abused to disclose a user's identity. An identification attack could be successfully performed by exploiting a UI Redressing flaw affecting web resources that include, for example, the name or the e-mail address of the victim.

A series of vulnerabilities are presented below in order to exemplify some of these attacks. The first issue affects a Google's web application: an authenticated Google user can be attacked by abusing a UI Redressing vulnerability related to the support.google.com domain. As shown in Figure 1, no X-Frame-Options header is adopted, thus allowing the cross-domain extraction of personal data such as:

• Victim's e-mail address;
• Victim's first and last name;
• Victim's profile picture URL.

Figure 1 - Google Support vulnerable to UI redressing attacks.

A Proof of Concept exploit can be downloaded here. The following is a video demonstrating the attack:

Similar vulnerabilities have been found on other popular web applications. The following is a list of identified vulnerable web resources, exposing user's data:

Microsoft Profile (First name, last name, e-mail address, etc - Figure 2)

• https://profile.live.com/home/Services/?view=manage&productid=connectedtoprofile

Figure 2 - Microsoft Profile web resource vulnerable to UI Redressing attacks.

Yahoo! (e-mail address, first name, birth date, sex, etc - Figure 3):

• http://profile.yahoo.com/y/edit/

Figure 3 - Yahoo! web resource vulnerable to UI Redressing attacks.

 

Beyond the iframe-to-iframe extraction method

The Google Chrome web browser seems to have defeated any extraction methods, denying the use of the view-source handler and disallowing cross-origin drag&drop. Despite these adverse conditions, I identified some attack scenarios where a UI Redressing issue could be still performed in order to extract sensitive data. Once again, the method is extremely simple. Instead of a cross-origin drag&drop, the victim is tricked to perform a same-origin action, where the dragged content belongs to a vulnerable web page of the targeted application and the "dropper" is a form (text area, input text field, etc.) located on the same domain. Using a site's functionality that allows publishing externally-facing content, it is still possible to extract information. Under these circumstances, Chrome will not reasonably deny the same-origin drag&drop, thus inducing the victim to involuntary publish sensitive data. As a matter of fact, the attacker is exploiting a subsequent clickjacking vulnerability on the same domain, which causes the publication of the personal information. I refer to this kind of attack chain as a "bridge" that allows the attacker to move sensitive data from being private to public, while remaining on the same domain. Then, the attacker can simply access the (now) public information to obtain the extracted data. It should be outlined that the technique requires two vulnerabilities: a web resources that is not protected by the X-Frame-Options (or uses a weak frame-busting code) and a site's functionality that is affected by clickjacking.

The following list summarizes a series of functionalities that could be abused to extract the sensitive data:

• Forum's post mechanism;
• "comment this item" functionalities;
• Public profile information updating function (or any "update function" that involves public available data - e.g. administrative functions that cause the updating of the web site's content);
• Messaging functionalities (e.g. from the victim to the attacker);

The proposed method has been successfully applied against Google Chrome version 23.0.1271.97, targeting the Amazon web application. Amazon exposes a series of web resources that include user's data - such as the name, e-mail address, mobile number and "address book" details - that are not protected with both X-Frame-Options header or any frame-busting mechanism. As an example, the following vulnerable URL includes Amazon's user first name, last name and e-mail address:

• https://www.amazon.com/gp/css/account/info/view.html?ie=UTF8&ref_=ya_20

A second issue on the comment function - our "bridge" - can be abused to publish the user's information as a comment for an Amazon item (e.g. a book), previously known by the attacker, and whose comments are "monitored". The following steps summarize the exploitation phases:

1. The exploit frames both the vulnerable URL and the comment form of a attacker-chosen Amazon's book;
2. The victim is triggered to drag his data and drop the information to the framed comment form;
3. A clickjacking attack is then performed against the "Post" mechanism, in order to publish the dropped data;
4. At that point the attacker can access all personal details by simply visualizing the submitted comment of the Amazon's item.

The exploit code can be download here, while the following is a video of the described attack:

Update - media coverage: http://threatpost.com/chrome-clickjacking-vulnerability-could-expose-user-information-google-amazon-010213/77358

UI Redressing Mayhem: HttpOnly bypass PayPwn style

In the previous post, a new cross-domain extraction method - affecting the latest version of the Mozilla Firefox browser - has been presented. The iframe-to-iframe technique was successfully used in a UI Redressing attack affecting LinkedIn. Today, I'm introducing an instance of the aforementioned method that involves a known Apache Web Server security issue, in order to steal session cookies that are protected by HttpOnly flag, thus allowing the attacker to perform Session Hijacking attacks. A new attack targeting PayPal systems will be also presented.

CVE-2012-0053: HttpOnly bypass and beyond

In January 2012 - even if the Apache defect was known and exploited for a while - Norman Hippert disclosed CVE-2012-0053 bug affecting the Apache Web Server. The software was not able to correctly restrict an header field information disclosure in case of overlong or malformed HTTP requests. The vulnerability could be effectively combined with a Cross-Site Scripting attack to bypass the protection mechanism introduced by the HttpOnly flag and steal any session token stored as cookies value. Infact, an XSS vector could manipulate the document.cookie object to set an overlong cookie field, and forward a malformed request to the affected Apache Web Server with the intention to trigger the error message and extract the desiderated session cookies. The Apache bug can be abused in a series of attack scenarios such as the following:

• Bypassing HttpOnly flag with a XSS vulnerability on the same domain that is affected by the CVE-2012-0053;
• Bypassing the limitation introduced by cookie path whereas the XSS vulnerability affects a web resources that resides outside the defined path itself;
• Bypassing HttpOnly flag if a XSS vulnerability is found on any subdomains of the host that is affected by the Apache disclosure issue, if exploited in conjunction with a UI Redressing attack - that allows the cross-domain content extraction of the information included in the triggered Apache error message.

It should also be noted that the Apache Web Server is often used as a reverse proxy configuration. As a result, any session object on any server-side technology, could be attacked with the described vectors.

Smashing PayPal for Fun but.. NO Profit

 

During my security research on UI Redressing attacks I found multiple PayPal subdomains (e.g. https://b.stats.paypal.com) affected by the Apache disclosure bug as detailed in Figure 1 and Figure 2.

Figure 1 - HTTP request with the overlong cookie.

Figure 2 - Apache error message with the disclosure of the malformed Cookie header.

Despite in the first instance the bug could appear as useless, I found that the PayPal application - www.paypal.com - delivers the session cookies defining the domain to .paypal.com (Figure 3 and Figure 4).

Figure 3 - Post-authentication cookies delivery.

Figure 4 - Cookies delivered to the personal.paypal.com subdomain.

The highlighted security issues could be abused to attack authenticated PayPal users, implementing the mentioned UI Redressing attacks combined with the cookie disclosure bug. But.. I had a problem: I had no XSS vulnerability on any PayPal web application - not that there're not! I was able to circumnavigate the limitation identifying another vulnerability on a different PayPal subdomain, that allowed me to define a monster cookie with a single HTTP request. As first, please note the following URL:

• https://history.paypal.com/helpcenter/script/pphc_rating.js.jsp?locale=&_dyncharset=UTF-8&countrycode=CA&cmd=_AAAAKKKKKKAAAAKKKKKK[..very long string here...]KKKKKKAAAAKKKKKKAAAAKKKKKK&serverInstance=9002&no_strip= 

As detailed in Figure 5, the navigation of the above URL involves the setting of the cookie named navcmd and then a bit of client-side black magic defines two new cookie fields named s_sess and s_pers (Figure 6) that complete the desiderated malformed HTTP request.

Figure 5 - Cookie defined with attacker-controlled input.

Figure 6 - Final monster cookie.

7350PayPwn

 

The exploitation is now trivial. The following are the logical steps implemented by the Proof of Concept exploit:

1. The exploit triggers the victim to open an under pop (Figure 7) web page that generates the monster cookie - with domain=.paypal.com - involving the history.paypal.com application;
2. The https://b.stats.paypal.com is then framed thus inducing the forward of a malformed HTTP request that triggers the disclosure of the Cookie header, containing the PayPal account's session cookies;
   
3. The malicious page allows the victim to play the d&d game with the extraction of the secret session cookies.

Figure 7 - Pop-under page with the navigation of the monster cookie's generation URL.

The attacker now holds the cookies that can be used to perform a Session Hijacking attack against the victim's PayPal account. A working Proof of Concept has been developed and can be download here. The following is a video that illustrates the described attack:

UI Redressing Mayhem: Firefox 0day and the LeakedIn affair

In the past weeks I worked on UI Redressing exploitation methods. The UI Redressing Mayhem series is going to illustrate the results of my research, presenting 0day exploiting techniques and several vulnerabilities that involve high-profile web applications. Each post of the series will also provide detailed information about the vulnerabilities and techniques, together with working Proof-of-Concept exploits.

The following article will detail a previously unknown Mozilla Firefox  vulnerability that affects the latest version (v.17.0.1) of the Mozilla web browser and allows malicious users to perform cross-domain extraction of sensitive data via UI Redressing vectors.

It was a dark and stormy night...

My security research on UI Redressing exploitation techniques grounds its roots in a web application penetration test where I was asked to exploit a UI Redressing bug with the explicit constraints to target Mozilla Firefox users. My objective was to achieve the cross-domain content extraction of an anti-CSRF token, in order to trigger the update of the victim's profile e-mail address: the powerful double drag&drop method was found to be appropriate in that context. To the best of my knowledge, the method was first introduced by Ahamed Nafeez and is based on the possibility to perform a drag&drop action between a framed web page, which displays the "sensitive" contents and is not protected by the X-Frame-Options header, and the framing page (the "dropper" page), which receives and stores the extracted content. The view-source handler is used here to bypass any framebusting code.

The main problem with my exploit development, during the penetration test, was that the drag&drop method was recently killed by Mozilla. An interesting solution to the Mozilla fix is the fake CAPTCHA method that was introduced by Krzysztof Kotowicz — and demonstrated to be effective against Facebook and Google eBookstore — but I chose the hard way and tried to bring the drag&drop method back to the masses: so please welcome the iframe-to-iframe cross-domain extraction method.

The iframe-to-iframe extraction method

The extraction method is extremely simple: instead of performing a drag&drop action of sensitive data, from a framed vulnerable web page to the framing one (attacker-controlled), the victim is tricked to visit a malicious html page that includes two iframes: the vulnerable page - where the sensitive content resides - and another attacker's page that is used to drop the extracted content (Figure 1). Firefox is not able to block this kind of attack because no check on cross-domain drag&drop between iframes is performed. As mentioned before, the method was tested against Mozilla Firefox version 17.0.1 - the latest stable release at the time of writing. The iframe-to-iframe technique was also tested against Google Chrome but the browser has been proved robust to the proposed attack.

Figure 1 - iframe-to-iframe d&d extraction method.

The iframe-to-iframe method re-introduces the possibility to abuse the Firefox drag&drop mechanism to perform a cross-domain data extraction. Let me now introduce an high-profile vulnerability and attack that targets the LinkedIn application implementing the proposed method.

All your LinkedIn accounts are belong to us

LinkedIn implements a stateless anti-CSRF mechanism that associates tokens to the HTTP requests that result in a change of the remote application state, such as the update of a user's profile information (e.g. job title or the login e-mail address). A stateless anti-CSRF method is generally based on a secret token, delivered as a cookie parameter, and a token which is included in every state-changing HTTP request: the remote web application considers as genuine exclusively the HTTP requests that have the same token value for both the cookie and HTTP parameter. Otherwise, a request is considered untrusted and it is not computed. The LinkedIn's anti-CSRF mechanism involves a cookie parameter called JSESSIONID and an HTTP parameter named csrfToken in order to store the secret tokens (Figure 2). A stateless mechanism can be easily bypassed with well known web hacking techniques.

Figure 2 - anti-CSRF tokens.

For example, the attacker could abuse a Cross-Site Scripting issue on both www.linkedin.com or any LinkedIn's subdomains to poison the cookie parameter JSESSIONID and bypass the mechanism — this attack is also known as Cookie Tossing. During my security research I found a vulnerable LinkedIn's page that includes the anti-CSRF token within the HTML code, despite not being protected by the X-Frame-Options header. Under these circumstances, the iframe-to-iframe method can be used to attack authenticated LinkedIn users and steal their secret token in order to perform different kind of malicious actions on the victim's profile. The following URL refers to the LinkedIn vulnerable web resource as detailed in Figure 3:

• http://www.linkedin.com/companies?trk=hb_tab_compy 

Figure 3 - Vulnerable LinkedIn web resource.

The vulnerability can be easily abused to craft a UI Redressing exploit that triggers the victim to drag&drop the anti-CSRF token. The token can then be abused to edit any information on the victim's profile and even to reset the account password. In order to demonstrate the effectiveness of the attack I developed a fully working Proof of Concept exploit that adds the attacker's e-mail as a trusted address to the victim's profile and verifies the e-mail itself. At that point, the attacker can easily reset the victim's password using LinkedIn password reset mechanism.

The following are the logical steps implemented by the Proof of Concept exploit:

1. The malicious page frames both the LinkedIn vulnerable page and the attacker-controlled "dropper" page;
2. The malicious page allows the victim to play the d&d game, which extracts the anti-CSRF token;
3. The malicious page can now bypass the anti-CSRF protection and adds a new e-mail address to the victim's profile. The action involves the forwarding of a confirmation e-mail from LinkedIn system to the attacker box: an activation URL is included;
4. The exploit interacts with an attacker's script — /linkedin/linkedin.php — which accesses the attacker's mail box via IMAP and waits for the Linkedin activation e-mail. Once obtained the e-mail, the URL is returned back to the malicious page, which is still loaded by victim's web browser;
5. The script can now simulate the navigation of the fetched URL in order to confirm the new address.

The attacker can now reset the victim's account password abusing the password reset functionality, where he will type the e-mail address previously added to the targeted profile. Figure 4 highlights the different HTTP requests exchanged between the attacked web browser, the attacker's servers and the LinkedIn web application, in order to achieve the password resetting.

Figure 4 - Sequence diagram detailing the attack.

A working PoC has been developed and can be downloaded here. The following is a video of the attack:

 

Beyond the Mayhem

LinkedIn Team was informed about this attack scenario. The following are a series of suggestions that should prevent this kind of attacks:

• Protect every web resource that includes anti-CSRF tokens with the X-Frame-Options header. Nowadays, this mechanism is available in all major browsers;
• Consider to adopt a stateful anti-CSRF mechanism that should not perform the validation on the basis of potentially attacker-controlled inputs.