Rootkit scans are the best attempt to detect a rootkit infection, most likely initiated by your AV solution. A surefire way to find a rootkit is with a memory dump analysis.
You can always see the instructions a rootkit is executing in memory, and that is one place it can't hide. Rootkit Remover is a standalone utility used to detect and remove complex rootkits and associated malware.
You can check for rootkits by running the Windows Defender Offline scan. Several companies also offer free rootkit scanners.
Kernel mode. Kernel rootkits can be especially difficult to detect and remove because they operate at the same security level as the operating system itself, and are thus able to intercept or subvert the most trusted operating system operations. A Logic Bomb is a piece of often-malicious code that is intentionally inserted into software. Logic bombs execute their functions, or launch their payload, once a certain condition is met such as upon the termination of an employee.
In computing, a Trojan horse, or Trojan , is any malware which misleads users of its true intent. Rootkits , are hidding in your OS system core, and trojan can hide or not, and a trojan can give access to your computer to a hacker or identity theft, and a rootkit mayorly just mess up with your computer. The whole purpose of a rootkit is to protect malware. Think of it like an invisibility cloak for a malicious program. This malware is then used by cybercriminals to launch an attack. The malware protected by rootkit can even survive multiple reboots and just blends in with regular computer processes.
By comparison, the Melissa virus prompted calls from about 50 sites representing hundreds of affected PCs. The virus may overwrite the system's hard drive, erasing everything on it. CIH may also attack the portion of the machine's BIOS that affects the start-up sequence, making the computer unusable. Wait for security researchers to find some vulnerability in the ransomware that would allow you to decrypt files without paying.
This turn of events is possible but not very probable: out of thousands of known ransomware variants, only dozens were found to be decryptable for free. Use paid services for decryption.
For example, antivirus vendor Dr. Web offers its own decryption services. They are free for users of Dr. Web Security Space and some other Dr. Web have been installed and running at the time of encryption more detail. According to Dr. Other ways to recover encrypted files: Restore from backup. Just scan your computer with a couple of AVs and anti-malware programs or reinstall operating system, and then restore from backup. Even if encrypted files were already synced to the cloud, a lot of cloud services keep old versions of altered files for some time usually 30 days.
Recover Shadow Volume Copies of your files if those are available — ransomware usually tries to delete them too. Volume Shadow Copy Service VSS is a Windows technology that periodically creates snapshots of your files and allows you to roll back changes made on those files or recover deleted files. Use file recovery software. On HDD however, it rather gets marked as deleted, and space it occupies on a hard drive — as available for writing, but the data is still there and usually recoverable by special software.
Processor is further coupled to persistent storage via transmission medium According to one embodiment of the disclosure, persistent storage may include stalled processing analysis logic and a data store In general, stalled processing analysis logic is configured to monitor and alter operating parameters for one or more VM-based analysis environments in order to improve reliability in detecting time-bomb malware.
The results of the analysis are stored within data store More specifically, stalled processing analysis logic comprises sleep analysis logic , call analysis logic , comparison logic , time adjustment logic , instruction pointer analysis logic , and processor statistic monitoring logic Herein, both sleep analysis logic and call analysis logic are configured to address an event where a series of successive Sleep function calls are used to stall processing of the incoming content. As an example, sleep analysis logic may be configured to monitor the number of Sleep calls, the Sleep intervals and the cumulative Sleep time.
The call analysis logic may be configured to perform the same general functionality in monitoring the number of function calls made globally or to a particular call site as well as the cumulative delay incurred by initiation of function calls. Optionally working in concert with sleep analysis logic and call analysis logic , the time adjustment logic is configured to alter the time interval returned back to the content running in the VM-based analysis environment e.
More specifically, sleep analysis logic is configured with one or more counters that are used to count the number of Sleep request messages initiated by the content under analysis for subsequent comparison, using comparison logic e.
Additionally, the sleep analysis logic may be further configured with one or more counters that are used to compute the cumulative amount of time e. The cumulative amount of time is subsequently compared, using comparison logic , to a second threshold value that is different than the first threshold value. The second threshold value may be set to a time value less than the average amount of time permitted for analysis of the content within a VM-based analysis environment 1.
Call analysis logic is configured with one or more counters that are used to count the number of function calls initiated by the content under analysis, which is subsequently compared with a third threshold value stored in data store using comparison logic The number of function calls may be based on either i a global basis e. It is contemplated that the third threshold value may differ from the first and second threshold values, and the value may be based at least in part on the type of function call.
For instance, the GetLocalTime function call may be analyzed with greater scrutiny as this API function call tends to be a common choice for repetitive call type of evasion. Call analysis logic may be further configured with one or more counters that are used to monitor the cumulative amount of time that the called functions would need for execution of the called function.
Using comparison logic , the cumulative amount of time is subsequently compared to a fourth threshold value stored in data store This allows the reporting module to assign weights intelligently e.
As further shown in FIG. The instruction pointer analysis logic is configured to periodically check, during processing of the content under analysis, whether the instruction pointer has remained within one or more prescribed address range s over a prolonged period of time. This check is conducted in order to determine if the content includes time-bomb malware adapted to perform an instruction-based loop to evade analysis within the VM-based environment. If the instruction pointer analysis logic determines that the instruction pointer continues to remain within a particular address range, the processor utilization measured by processor statistic monitoring logic is greater than a prescribed value, and no other exploits have been detected, the instruction pointer analysis logic determines that the content under analysis is associated with time-bomb malware.
According to one embodiment of the disclosure, at least the sleep analysis logic , call analysis logic and time adjustment logic are implemented as part of the VM.
The comparison logic , instruction pointer analysis logic and processor statistic monitoring logic may be placed within the VM or outside the VM. Dynamic threshold generation logic comprises logic that dynamically alters the threshold values utilized by the sleep analysis logic and call analysis logic The dynamic nature of the threshold values prevents malware writers from altering malware to circumvent established thresholds, if such thresholds are discovered.
Another optional logic implemented within MCD system 1 is the call site management logic The call site management logic is configured to maintain a finite number of call sites as part of a table. If the table is full and a request for a new call site is made, the call site management logic determines if the new call site is associated with a larger processing time requirement than another call site within the table.
If so, the new call site is substituted for that call site. If not, the new call site is not placed within the table. However, cumulative threshold is updated accordingly. VMs within the analysis environment are based on these software profile s. Thereafter, the VM s perform operations on the suspicious content and analyzes the results of these operations to determine if any exploits are present block These operations may include Sleep analysis, Call analysis and profiling e. If no exploits are detected, no further time-bomb analysis is needed block Otherwise, according to one embodiment of the disclosure, one or more counters are initiated during run-time of the content under analysis.
Where the Sleep activity exceeds a prescribe threshold, a determination is made that the content under analysis includes time-bomb malware blocks and Such shortening of the Sleep time, which is unbeknownst to the content under analysis, alters the processing time frame for the VM environment and allows the VM to monitor and report the particulars behind the time-bomb malware attack.
If the Sleep activity remains below the prescribed threshold, the VM continues to operate as normal block The counter s may monitor the number of repeated function calls to a particular API. Where the number of function calls exceeds a prescribe threshold, a determination is made that the content under analysis includes time-bomb malware blocks and As a result, the call analysis logic is adapted to emulate compliance with requested function calls by responding to these function calls, sometimes with a shortened call response wait time block Such shortened response time, which is unbeknownst to the content under analysis, alters the processing time frame for the VM environment to allow the VM to monitor and report the particulars behind the time-bomb malware attack.
If the number of function calls to a particular API does not exceed a prescribed threshold, the VM will continue to operate as normal block Otherwise, according to one embodiment of the disclosure, the instruction pointer analysis logic profiler undergoes operations to determine if the instruction pointer utilized during processing of the content under analysis is frequently located into the same memory address or a particular range of memory addresses block If not, no time-bomb malware is detected by the VM operating within the analysis environment of the analysis engine.
In the event that the profiler detects continued presence of the instruction pointer as described above, a determination is made by the processor statistics monitoring logic profile if processor utilization is greater than a prescribed operating threshold blocks - If so, and no other malicious activity is detected, a determination is made that the content under analysis includes time-bomb malware block If the processor utilization is below the prescribed threshold or other malicious activity is seen, then no time-bomb malware is detected.
Hence, the VM will continue to operate as normal block In the foregoing description, the invention is described with reference to specific exemplary embodiments thereof. It will, however, be evident that various modifications and changes may be made thereto without departing from the broader spirit and scope of the invention as set forth in the appended claims. What is claimed is: 1. A system comprising: one or more counters;.
The system of claim 1 , wherein the one or more virtual machines being configured to monitor time intervals for Sleep request messages initiated during processing of the content and identifying the content as including malware if a combined delay for the Sleep request message exceeds the first time period. The system of claim 1 , wherein the one or more virtual machines being configured to monitor time intervals for Sleep request messages initiated during processing of the content and identifying the content as including malware if one of the time intervals exceeds the first time period.
The system of claim 1 , wherein the one or more virtual machines being configured to further monitor the one or more events being a number of function calls initiated during processing of the content and identifying the content as including malware if the number of function calls exceeds a threshold value. The system of claim 1 , wherein the one or more virtual machines being configured to further monitor the one or more events by determining if, during processing of the content, the instruction pointer is repeatedly directed to a specific address or address range and identifying the content as including malware if the instruction pointer is repeatedly directed to the specific address or address range.
The system of claim 1 , wherein the first time period has a duration that is dynamically set. The system of claim 1 , wherein the one or more virtual machines being configured to maintain and monitor values of time intervals for Sleep calls per call site, initiated during processing of the content and identifying the content as including malware if one of the time intervals exceeds a predetermined time period.
The system of claim 1 , wherein the one or more virtual machines being configured to maintain and monitor values of call counters for certain functions per call site, initiated during processing of the content, and identifying the content as including malware if one of the call counters exceeds the a predetermined count threshold. The system of claim 1 further comprising a reporting module being configured to differentiate call sites based on module names and assign weights accordingly and identifying the content as including malware if a higher count is associated with a call site residing in the content under analysis.
The system of claim 1 further comprising a heuristic engine being configured to identify delay hotspots and identifying the content as including malware if one of a plurality of time intervals associated with the delay exceeds a predetermined time period.
The system of claim 1 , wherein the comparison logic includes one or more comparators. A system comprising: one or more processors;. The system of claim 12 , wherein the one or more virtual machines being configured to monitor time intervals for one type of event being one or more Sleep request messages initiated during processing of the received content and identifying the content as including malware if a total delay requested by the one or more Sleep request messages exceeds the second threshold being a first predetermined time period.
The system of claim 12 , wherein the one or more virtual machines being configured to monitor time intervals for one type of event being one or more Sleep request messages initiated during processing of the content and identifying the content as including malware if one of the time intervals exceeds a first predetermined time period.
The system of claim 12 , wherein the one or more virtual machines being configured to further monitor the number of events being a number of function calls initiated during processing of the content and identifying the content as including malware if the number of function calls exceeds the first threshold. The system of claim 12 , wherein the one or more virtual machines being configured to further monitor an event by determining if, during processing of the content, the instruction pointer is repeatedly directed to a specific address or address range and identifying the content as including malware if the instruction pointer is repeatedly directed to the specific address or address range.
The system of claim 12 , wherein the second threshold has a duration that is dynamically set. The system of claim 12 , wherein the one or more virtual machines being configured to maintain and monitor time intervals for Sleep calls per call site, initiated during processing of the content and identifying the content as including malware if one of the time intervals exceeds a predetermined time period. The system of claim 12 further comprising a reporting module being configured to differentiate call sites based on module names and assign weights accordingly and identifying the content.
USB2 en. EPB1 en. WOA1 en. USB1 en. Synchronizing a honey network configuration to reflect a target network environment.
System, apparatus and method for conducting on-the-fly decryption of encrypted objects for malware detection. System and method of detecting delivery of malware based on indicators of compromise from different sources. Electronic device for aggregation, correlation and consolidation of analysis attributes. System and method for detecting anomalous behaviors using a virtual machine environment.
Systems and methods for identifying detection-evasion behaviors of files undergoing malware analyses. Systems and methods for categorizing virtual-machine-aware applications for further analysis. System and method for offloading packet processing and static analysis operations. System and method for detecting file altering behaviors pertaining to a malicious attack.
0コメント