system: You are an expert security code reviewer. You will be shown a source code file along with a multi-select question listing several CWE (Common Weakness Enumeration) categories. Your task is to identify which of the listed CWEs are present in the code.

OUTPUT FORMAT: Respond with the letter(s) of all correct options, sorted alphabetically and comma-separated, wrapped in a single \boxed{...}. Examples: `\boxed{A}` for one correct, `\boxed{A,C}` for two, `\boxed{A,C,E}` for three. Output the boxed answer ONLY -- no explanation, no other text.

user: ```python
# Quickie D3JS-NX interface for Jupyter Notebooks
# Copyright (c) Nick Timkovich 2015
# MIT Licensed
from __future__ import absolute_import, division, print_function
import random
import json

from IPython.display import HTML
import jinja2

__all__ = ['nx_force']

_LETTERS = 'bcdghjklmnpqrtvwyz'
_CHARS = _LETTERS + '346789'

_ENV = jinja2.Environment()

_TEMPLATE = _ENV.from_string('''
<style>
    .node {
      stroke: #fff;
      stroke-width: 1.5px;
    }

    .link {
      stroke: #999;
      stroke-opacity: .6;
    }

    .node text {
      pointer-events: none;
      font: 10px sans-serif;
      color: #000;
      stroke-width: 0;
    }
</style>
<script>
+function() {
    var options = {
        'divid': '#{{ divid }}',
        'data': {{ data }},
        'width': {{ width }},
        'height': {{ height }},
        'linkdistance': {{ linkdistance }}
    }

    if (window.d3 === undefined) {
        console.log('Loading D3 from CDN');
        $.getScript('https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.7/d3.js')
            .done(function() {
                plot_force(options);
            });
    } else {
        plot_force(options);
    }

    function plot_force(o) {
        var color = d3.scale.category20();

        var svg = d3.select(o.divid).append("svg")
            .attr("width", o.width)
            .attr("height", o.height);

        var force = d3.layout.force()
            .charge(-120)
            .linkDistance(o.linkdistance)
            .size([o.width, o.height])
            .nodes(o.data.nodes)
            .links(o.data.links)
            .start();

        var link = svg.selectAll(".link")
                .data(o.data.links)
            .enter().append("line")
                .attr("class", "link")
                .style("stroke-width", function(d) {
                    return Math.sqrt(d.value);
                });

        var node = svg.selectAll(".node")
                .data(o.data.nodes)
            .enter().append("g")
                .attr("class", "node")
                .call(force.drag)

        node.append("circle")
            .attr("r", 5)
            .style("fill", function(d) { return color(d.group); });

        /*node.append("title")
            .text(function(d) { return d.name; });*/

        {{ insert_a }}

        force.on("tick", function() {
            link.attr("x1", function(d) { return d.source.x; })
                .attr("y1", function(d) { return d.source.y; })
                .attr("x2", function(d) { return d.target.x; })
                .attr("y2", function(d) { return d.target.y; });

            node.attr("transform", function(d) {
                return "translate(" + d.x + "," + d.y + ")";
            });
        });
    }
}();
</script>
<div id="{{ divid }}">
</div>
'''.strip())

_LABEL_INSERTS = {
    None: '',
    'always': '''
        node.append("text")
            .attr("dx", 12)
            .attr("dy", ".35em")
            .text(function(d) { return d.name; });
        ''',
}


def _rand_id(len=8):
    return (random.choice(_LETTERS)
            + ''.join(random.choice(_CHARS) for _ in range(len - 1)))


def nx_force(G, size=(600, 400), labels=None, linkdistance=30):
    """
    Provided a NetworkX graph, render it in JS using D3js.

    *size* is a 2-ple with the width and height in pixels. *labels* can be
    ``None``, ``'always'``. *linkdistance* is the relaxed link distance.
    """
    data = {
        'nodes': [],
        'links': [],
    }
    node_index_map = {}
    for i, (node, ndata) in enumerate(G.nodes_iter(data=True)):
        node_index_map[node] = i
        data['nodes'].append({
            'name': str(node),
            'group': ndata.get('group', 0),
        })
    for u, v, edata in G.edges_iter(data=True):
        data['links'].append({
            'source': node_index_map[u],
            'target': node_index_map[v],
            'value': edata.get('weight', 1),
        })

    divid = 'd3shim-' + _rand_id()
    html = _TEMPLATE.render(
        width=size[0],
        height=size[1],
        divid=divid,
        data=json.dumps(data),
        insert_a=_LABEL_INSERTS[labels],
        linkdistance=linkdistance,
    )
    # display(HTML(html))
    # return divid
    return HTML(html)

```

Which of the following CWE vulnerability categories are present in this code? Multiple options may be correct.

  A) CWE-943: Improper Neutralization of Special Elements in Data Query Logic
  B) CWE-1333: Inefficient Regular Expression Complexity
  C) CWE-732: Incorrect Permission Assignment for Critical Resource
  D) CWE-918: Server-Side Request Forgery (SSRF)
  E) CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
  F) CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
Answer: E