Download dangerous files through a virtual machine

Using SCP to transfer the files is the easiest way to get the log directory and files down to your workstation while also being secure. The -r flag instructs SCP to recursively copy the files and directories from the point of the directory listed in the command. Also notice that the command-line syntax is similar to a cp copy command. Skip to main content. This browser is no longer supported. Download Microsoft Edge More info. Contents Exit focus mode. In the example, we assume we have N VMs and M physical machines.

We can use vulnerability scanner tools, such as Nessus and Qualys, to generate the vulnerability list for every VM. The CVSS score uses an interval scale of 0, 10 to measure the severity of vulnerabilities. There are different ways to calculate how the guest VMs can affect the security of hypervisors. In this paper, we mainly consider the VM with the highest risk since this may be the most vulnerable attacking surface to the hypervisor.

If an attacker compromises a VM, he can compromise, with enough time, other co-resident VMs eventually. So a VM can survive only if all other co-resident VMs can survive. Considering the cascades [ 13 ] in the network, giving a VM, a depth first algorithm can be applied to build all possible attack paths.

In our previous work, we also discussed how to evaluate risks of being attacked based on Markov Chains [ 14 ]. Thus, there are different ways to evaluate the risk levels based on network connections. In this paper, we simply consider the risk caused by only direct network connections for simplicity, while other approaches can also be applied. Assume that we have N VMs and M physical machines. Our goal is to find solutions to minimize these values.

Resource Wastage. Minimizing resource wastage, while complying with the constraints, is the second objective in VMP optimization. In this paper, we consider the wastage of multiple resources, including CPU, memory, and disk. In stead of using one value to measure the resource wastage, we use a vector to represent the resources wastage. Note that our system does not limit the number of objectives or constraints. The users can add more objectives or constraints, such as energy or migration cost, based on their preferences.

With the proposed security metric of VMs, we can quantify the risk level of a cloud. As a typical multi-objective optimization problem, the objectives may conflict with each other. For example, if we place more VMs on a physical server, it will be less secure due to co-residency problem.

However, it can reduce the resource wastage and network traffic. It is impractical to always find the optimal solution minimizing all objectives.

Using EMOA, we can obtain Pareto-optimal solutions balancing on the objectives of security, network traffic and resource utilization. The challenge is that the security metrics can only be evaluated after the placement is specified. For example, in a specific placement scheme, a unique attack path exposed by co-residence may disappear in a different placement.

Therefore, there is no generic function mapping a placement scheme into a security assessment value. As a result, we cannot use any existing multi-objective programming solutions to solve our problem.

Furthermore, we have complicated security strategies in each placement generation, we have to design a new crossover and a new mutation procedure in the EMOA algorithm. In an initialization phase , the consideration for migration cost can be avoided. Our goal is to search for the best possible placement plan based on the multi-objectives requirement. The crossover operation is used to improve the overall efficiency. In the re-optimization phase , which is triggered by adding VMs or removing VMs, the migration cost is considered as an important factor in the mutation operation to limit the number of migrating VMs in switch function of Algorithm 3.

Note that our goal is to improve the survivability of entire cloud, so we do not optimize our solution for a specific VM. Therefore, our approach may lower the security level of a specific VM, while the overall security level of whole cloud can still be improved. Isolated Zones. Since the security is a key factor in the placement generation, we introduce isolated zones in our algorithm to accommodate different security demand. Physical machines with the highest hypervisor risk levels are put into isolated zones.

The most dangerous VMs and VMs connected to them are placed into the isolated zones by priorities. The purpose of the isolated zones is to isolate the most dangerous VMs first and reduce the number of attack paths through network connections.

If all physical machines use the same copy of hypervisor, the vulnerabilities of all the hypervisors will also be the same. In such a situation, we have the following assumptions. Open image in new window The possibility to compromise any physical machine through the hypervisor attack surface for a specific VM is the same.

Open image in new window If the communication bandwidth between two VMs is larger than zero, the possibility to compromise one VM through another VM will be non-zero. We propose five security related strategies to reduce security risk during each placement generation. Placement strategy I: Put a VM into a physical machine which has network connections with it.

We have more strategies applied in the placement generation. Placement strategy II: high risk VMs should be put into the isolated zones.

Placement strategy IV: marked lowest and highest hypervisor risk physical machines should have a higher probability to be kept during crossover operation. Placement strategy V: If a VM on one physical machine has connection with a VM on a different physical machine, we should migrate one of them on to the same physical machine. When a Pareto-optimal solution is generated, our algorithm double checks the workload balance in every physical machine, migrating marked VMs among physical machines.

In the switch function of the algorithm, a VM can only be switched migrated to another physical machine to which it has network connections. The strategy is to guarantee that random evolving will not jeopardize the isolation of dangerous VMs and reduce unnecessary switching operation. We implemented our solution in Java. All input data are provided through configuration files. Multiple threads are used to improve the performance.

The vulnerability score is assigned based on the uniform distribution. Following the same method, we configure the physical machine. We test our implementation in a 8 core processor with 16GB memory. The overall performance of our algorithm is affected by the number of VMs, the number of physical machines, and the number of candidate placement generated in each generation. Figure 2 shows the computing time for each generation under the following setting: Open image in new window different placements are generated for each generation.

Open image in new window operations are done in each generation. With VMs and physical machines, each generation takes about 15—20 min. If we reduce the number of VMs to , each generation takes around 2 min. Security risk is a key consideration in VMP. To evaluate if our strategies can improve the security level of the entire cloud, we conduct the experiments considering risk level as the only objective in the placement. On its documentation page it reads:. The Custom Script Extension downloads and executes scripts on Azure virtual machines.

Scripts can be downloaded from Azure storage or GitHub , or provided to the Azure portal at extension run time. See for example this answer for more details on how to download a file from a blob. If you simply want to read the json file, then you can do as described here in this other answer.

Note : Invoke-RestMethod automatically converts the json response to a psobject. The 1. See the troubleshooting section in the Azure documentation for more information. Stack Overflow for Teams — Collaborate and share knowledge with a private group.

Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. By default, the virtual machine will have full read-write access to the folder. Be careful when using shared folders, though. One of the great things about virtual machines is that they operate in their own sandbox—isolated from your real computer. If your virtual machine becomes compromised, the malware could potentially escape your virtual machine by infecting files in your shared folders.

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